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Game Theory and Decision Theory - Science topic

Game Theory and Decision Theory is a game theory, decision theory, probability.
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Based on the literature review we get idea of moderators. But what we if want to introduce a new moderator in the literature.
1) What are the criteria for new moderator ?
2) How to theoretically support moderating variable ?
3) Is is necessary to adopt new moderating variable from same theory ?
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Game theory is a very promising technique to achieve optimal outcomes and can be applied to almost all concepts. I am trying to explore game theory for future purposes. However, as a beginner, I couldn't get very good resources regarding game theory.
Please share your resources (i.e., video or blog tutorial, research paper) regarding game theory, which covers the following things.
1. How to apply game theory?
2. How to prove optimal gain after applying game theory, (e.g., proving Nash equilibrium).
3. What are the state-of-the-art game theory techniques?
Thanks in advance.
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Anik Islam Abhi For example forecasting and game theory are both effective tools to support finance-related decision-making and reduce the impact of risk factors.
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what procedure and data should I use ?
how to structure the empirical study ?
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You may find this paper useful:
Stagnaro, M. N., Arechar, A. A., & Rand, D. G. (2017). From good institutions to generous citizens: Top-down incentives to cooperate promote subsequent prosociality but not norm enforcement. Cognition, 167, 212–254.
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Hello,
Can anyone share an article specifically on telehealth theory development and/or applications? Thank you!
Best,
Brooke
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Hi Brooke,
telehealth is a very broad domain. Do you have any particular interests? Maybe with regard to a specific technology or use case? I can provide you with some research once I know what you are aiming for.
Feel free to check out or research on primary care and the appplication of video consultaion:
Another of our articles is currently in press in JMIR, it deals with team-based care and delegation processes:
PS: The Journal of Medical Internet Research (JMIR) is a perfect start for research on that topic.
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Dear colleagues, friends, and professors,
As we know, we have very strong analytical approaches to control theory. Any dynamic decision-making process that its variables change in time could be characterized by state-space and/or state-action representations. However, we see very few control viewpoints for solving electricity market problems. I would like to invite you to share your thoughts about the opportunities, and limitations of such a viewpoint.
Thank you and kind regards,
Reza.
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I am currently doing my MBA dissertation on Coopetition within the Public sector.
Appreciate your expertise and opinion on how can Coopetition in the Public sector be successful and what are the main strategies to help it succeed (game theory, design thinking, innovation...etc). Coopetition is hands on in the Private sector and have been successful for years but not fully within the Public sector.
How can coopetition help governments be more Customer-centric?
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Aleksandr Sherstobitov great ideas and thank you for sharing them. The examples shared are spot on to coopetition yet to implement something similar in the public sector is different. If you have a utility company, an infrastructure company and an economic development company owned by the government, how can they all collaborate to give a single service to the public instead of having multiple channels (having the customer go to each individual company to get the same service)?
Christopher C Kelly Coopetition is a describe of cooperative competition. It is also a portmanteau of cooperation and competition.
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is there a logical approach for an answer to the non-conformance of Pareto optimal to Nash equilibrium ?
in-game theory context answer is: because of double-cross in Nash equilibrium which that not in Pareto optimal .
but can we find a logical language to Answering this question? for example with preferece modality, hybrid logic , epistemic logic,etc...?
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There are some literatures: one approach is to extend the game theoretical background taking role-switching. This approach is formulated in Kaneko-Kline (2015, International Game Theory Review Vo. 17, "Understanding the Other Through Social Roles". The main issue is how to understand the other person's thinking, but the paper shows some cooperative outcome results without assuming cooperation a priori (This is my answer to you question). The concept of role-switching comes from the tradition from Mead (1934, see the reference list in the KK paper). The other approach is found in Bachrach (1999, also in the list in the KK paper). Anyway, some additional assumtion or structure to the purely noncooperative setting is needed to have a cooperative outcome.
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Game theory is the study of mathematical models of strategic interaction between rational decision-makers.[1] It has applications in all fields of social science, as well as in logic and computer science. Originally, it addressed zero-sum games, in which one person's gains result in losses for the other participants. Today, game theory applies to a wide range of behavioral relations, and is now an umbrella term for the science of logical decision making in humans, animals, and computers.
Modern game theory began with the idea regarding the existence of mixed-strategy equilibria in two-person zero-sum games and its proof by John von Neumann. Von Neumann's original proof used the Brouwer fixed-point theorem on continuous mappings into compact convex sets, which became a standard method in game theory and mathematical economics. His paper was followed by the 1944 book Theory of Games and Economic Behavior, co-written with Oskar Morgenstern, which considered cooperative games of several players. The second edition of this book provided an axiomatic theory of expected utility, which allowed mathematical statisticians and economists to treat decision-making under uncertainty.
Game theory was developed extensively in the 1950s by many scholars. It was later explicitly applied to biology in the 1970s, although similar developments go back at least as far as the 1930s. Game theory has been widely recognized as an important tool in many fields. As of 2014, with the Nobel Memorial Prize in Economic Sciences going to game theorist Jean Tirole, eleven game theorists have won the economics Nobel Prize. John Maynard Smith was awarded the Crafoord Prize for his application of game theory to biology.
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The following is an article on game theory in the water field
Best Regards H. Naderpour
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Intellectually and psychologically, it is important to motivate architectural students in design studio. I propose to use ‘’Game theory’’ as a mechanism for practicing the formation of architectural composition. If you agree, how?
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Using Avatars, second life, and simulation, through creating complex, critical scenarios, for students in architecture can help to avoid mistakes and can have more holistic knowledge about safe architecture. Multi methodology approach for students can bring them close to deal with real life situations,.. more confidently. Aviation academic institutions use simulated scenarios, game based approaches, creating real life situations through project based learning and many more, to improve safety and prevent mistakes; because mistakes are fatal,... whether it is health care, aviation, architecture; so, there is load of literature that deals with things like improving critical thinking , problem solving, decision making among students, to better equip to deal with 21st century complex, uncertain environment.
" Air Force Using Avatar Technology for Training
Using lifelike video game-style technology, the avatars have true-to-life movements based on real people who model for the scenarios at AFRL’s Human Measurement and Signatures Intelligence program"
Kazan, R., Giacalone, M., Liu, J., Brogi, E., Cyr, S., & Hemmerling, T. M. (2019). Exposing medical students to various difficulty levels of simulated endotracheal intubations improves success rate: a randomised non-blinded trial. BMJ Simulation and Technology Enhanced Learning, bmjstel-2018.
Kapur, N., Parand, A., Soukup, T., Reader, T., & Sevdalis, N. (2015). Aviation and healthcare: a comparative review with implications for patient safety. JRSM open, 7(1), 2054270415616548.
Mota, M. M., & Flores, I. (2018). Revisiting the flaws and pitfalls using simulation in the analysis of aviation capacity problems. Case Studies on Transport Policy.
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In addition to this, I want to know which one of these two is better in terms of computational complexity and with respect to the game.
Thank you.
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Uniqueness of Nash Equilibrium is a desired property of games, but in most cases not ensured. Even for games in extensive form there may be multiple Nash Equilibria. Some of them may be not very plausible, because they inherit incredible threats. Therefore, additional features of equilibria have been considered, such as subgame perfectness (proposed by R. Selten as far as I know). This concept is also useful under computational aspects. Decision trees (of games in extensive form) can be efficiently inspected by the "Backward Induction Algorithm". In case of strict preferences of players on the terminal nodes of the decision tree subgame perfect equilibrium is unique. Nevertheless, even in this case, there may exist other (not subgame perfect) equilibria, which might be interesting, because they require some coordination between players. It may be attractive for specific groups of players to deviate from the subgame perfect solution in order to achieve a preferred outcome. Normally, this works only, if the threat posed by the player group is strong enough.
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How do you know that from the almost infinite action (toolbox), which action you need to choose (which is A , B etc..) to get the next step within the progress toward the target. (Starting point (like sitting in the armchair) -> A -> B -> C -> Cooked a Pizza or Went out of the room through the door )
What algorith/method the most effective when the task is NEW, so you need planning, don't just solve this with previous experience.
And this method should be universally applicable because the animals can solve problems with a very high diversity interval.
I hope you get is what the question is.
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Hi Axel,
the answer might easily fill some books, but in short:
1. You have to know the contents of your toolbox. On the lowest level, it might contain less than 50 tools (like in robotics programming: speed, accel, move, moves, appro, appros, depart, departs, break, wait, delay etc.) On the physical level, you get to know your toolbox as a child; on the cognitive level, during your education (which is a livelong process if you don't lead a boring life).
2. If you have done a similar task in the past: If the result was satisfactory then do it in the same way. If not then introduce some promising change.
3. If the task is new to you then search your memory for analogous tasks you have done successfully. (Cooking a soup might not be very different from cooking a pizza.)
4. If the task is completely new: Use your planning ability, i. e. simulate (in your mind) yourself and your environment based on your general experience. If you hit a solution then try to implement the solution in reality.
5. If the task is complex then apply "divide and conquer": Generate a hierarchy with the task as root and subtasks on lower levels. Stop when all subtasks forming leaves look feasible to you. It's the same as writing a program. If you don't know how to solve certain subtasks then you have to gain knowledge in this domain first before continuing the planning (or programming).
6. If the task is not only new (to you or anyone else) and solving the problem involves obviously some creative processes then your picture with the virtually infinite toolbox is correct: The solving process might include a lot of dead ends, it might take weeks, years, or decades, and you might not succeed at all.
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I want to compare two populations, but we can only measure 6 participants at a time at most (the total sample is larger of course). Therefore running the task classically is difficult.
A possible solution is having participants play against an algorithm (tit-for-tat, or adaptive pavlov). However, I can't find any literature of humans vs. algorithm in the prisoner's dilemma.
Am I missing something?
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Hi David,
Thanks for your input!
I looked at some of his research, yes.
I followed your suggestion and zeroed in on Axelrod's work. However, it's all simulations as well. Always algorithms vs. algorithms.
Oh well, thanks nevertheless!
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Suppose we have a set of players, i.e., {p1, p2, ..., pn} and each player has three different strategies, i.e., {s1, s2, s3}. They play m number of games. In each game, each player seeks to maximize its profit by selecting a strategy with highest playoff. The profit associated with each strategy is as follows.
1) Payoff for selecting strategy s1 is zero
2) Payoff for selecting strategy s2 is a real number, which is calculated using some formula f1
3) Payoff for selecting strategy s3 is also a real number, however, it is calculated using another formula f2
I want to prove the existence of Nash equilibrium when all the players select one of the available strategies.
I have searched on web and found several documents, however, I couldn't get a clear idea to prove it mathematically.
Any help is deeply appreciated. Please let me know if I have missed any information. Thank you in advance.
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@Felipe Please find attachment to see the formulas.
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Is there a distinction between strong or complete qualitative probability orders which are considered to be strong representation or total probability relations neither of which involve in-com parables events, use the stronger form of Scott axiom (not cases of weak, partial or intermediate agreements) and both of  whose representation is considered 'strong '
of type (1)P>=Q iff P(x)>= P(y)
versus type
(2) x=y iff P(x)=P(x)
y>x iff P(y)>Pr(x) and
y<x  iff P(y)<Pr(x)
The last link speaks about by worry about some total orders that only use
totallity A<=B or B<=A without a trichotomy https://antimeta.wordpress.com/category
/probability/page/3/
where they refer to:
f≥g, but we don’t know whether f>g or f≈g. S
However, as it stands, this dominance principle leaves some preference relations among actions underspecified. That is, if f and g are actions such that f strictly dominates g in some states, but they have the same (or equipreferable) outcomes in the others, then we know that f≥g, but we don’t know whether f>g or f≈g. So the axioms for a partial ordering on the outcomes, together with the dominance principle, don’t suffice to uniquely specify an induced partial ordering on the acti
.
 The both uses a total order  over
totality
A <=B or B >=A
l definition of equality and anti-symmetry,  A=B iff A<=B and B>=A
A<= B iff [A< B or A=B] iff not A>B
A>=B iff [A>B or A=B]iff not A<B
where A>B equiv B<A,and
A>=B  equiv B<=A iff (A<B)
where = is an equivalence relation, symmetric, transitive and reflexive
<=.=> are reflexive transitive, negative transitive,complementary and total
, whilst <, > are irreflexive and ass-ymetric,
transitive
A<B , B<C implies A>C
A<B B=C implies A>C
A<B, A<=B implies A>C
and negatively transitive
and complementary
A>B iff ~A<~B
<|=|>, are mutually exclusive.
and where equality s, is an equivalence class not denoting identity or in-comparability but generally equality in rank (in probability) whilst the second kind uses negatively transitive weakly connected strict weak orders,r <|=|>,
weak connected-ness not  (A=B) then A<B or A> B
whilst the second kind uses both trichotomous strongly connected strict total orders,  for <|=|>,.
(2) trichotomoy A<B or A=B or A>B are made explicit,  where the relations are mutually exclusive and exhaustive in (2(
(3) strong connectected. not  (A=B) iff A<B or A> B, and
and satisfy the axioms of A>= emptyset, \Omega > emptyset , \Omega >=  A
scotts conditions and the separability and archimedean axioms and monotone continuity if required
In the first kind <= |>= is primitive which makes me suspect, whilst in the second <|=|> are primitive.
Please see the attached document.And whether trich-otomoy fails
in the first type, which appears a bit fuzzier yet totality holds in both case A>=B or B<=B  where
What is unclear is whether there is any canonical meaning to weak orders (as opposed total pre-orders, or strict weak orders) .
In the context of qualitative probability this is sometimes seen as synonymous with a complete or total order. , as opposed to a partial order which allows for incomparable s, its generally a partial order, which allows for comparable equalities but between non identical events usually put in the same equivalence class (ie A is as probable as B, when A=B, as opposed, one and the same event, or 'who knows/ for in-comparability) Fihsburn hints at a second distinction where A may not be as likely as B, and it must be the case
not A>B and not  A< B  yet not A=B is possible in the second yet
A>= B or A<=B must hold
which appears to say that you can quasi -compare the events (can say that A less then or more probable,  than B ,but not which of the two A<B, A=B, , that is which relation it specifically stands in
but yet one cannot say that A>B  or A<B
)
and satisfy definitions
and A<=B iff A<B or A=B iff B>=A, iff ~A>=~B, where this mutually exclusive to A<B equiv ~B>~A
A>=B iff A>B or A<=B
iff iff B>=A where this mutually exclusive to A>B equiv ~B<~A
and both (1) and (2) using as a total ordering over >= |<=
(1)totalityA<= B or B<=A
(2)equality in rank and anti-symmetric biconditional  A=B iff A<=B and B>=A where = is an equivalence relation, symmetric, transitive and reflexive
(2) A<=B iff A<B or A=B, A>=B iff A>B or A<=B
(3) and satisfy the criterion that >|<|>=|<=,  are
complementary, A>B iff ~B<~A
transitive and negatively transitive,
where A<B iff B<A and where , =, <|> are mutually exclusive,
The difference between the two seem to be whether A>=B and A<= B is equivalent to A=B; or where in the first kind, it counts as strongly respresenting the structure even if A>=B comes out A>B because one could not specify whether A>B or A=B yet you could compare them in the sense that under <= one can say that its either less or equal in probability or more than or equal, but not precisely which of the two it is.
either some weakening of anti-symmetry of the both and the fact that the first kind use
whilst the less ambiguous orders trich-otomous orders use not  (A=B) iff A<B or A> B; generally trichotomy is not considered, when it comes to using  satisfying scotts axiom , in its strongest sense, for strict aggreement
and I am wondering whether the trich-otomous forms which appear to be required for real valued or strictly increasing probability functions are slightly stronger, when it comes to dense order but require a stronger form of scotts axiom, that involves <. > and not just <=.
but where in (1) these <=|>= relation is primitive and trich-otomoy is not explicit, nor is strong connected-ness whilst in (2)A neq B iff A>B or A<B
>|=|< is primitive and both
(1) totality A<= B or B<=A
(2) A<B or A=B or A>B are made explicit,  where the relations are mutually exclusive and exhaustive in (2(
and (2) trichotomy hold and are modelled as strict total trichotomous orders,
as opposed to a weakly connected strict weak order, with an associated total pre-order, or what may be a total order,
, or at least are made explicit.  I get the impression that the first kind as deccribed by FIshburn 1970 considers a weird relation that does not involve incomparables, and is consided total but A>=B and B<=A but one cannot that A is as likely as B, or that its fuzzy in the sense
that one can say that B is either less than or equal in probability to A, or conversely, but if B<= A one cannot /need not  whether say A=B or A<B,
not A=B] iff A<B or A>B
and strongly connected in the second.
where A=B iff A<=B and B>=A in both cases
where <= is transitive , negative transitive, complementary, total, and reflexive
A>=B or B<=A
are considered complete
and
y
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You are way too dispersed.
Try to undestand well the more basic stuff, one topic at a time.
Then move on.
Do not start from Gleason or weak measurements  for eample.
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I want to know how to run game theory inside WSN and which tool supports that?
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Please refer to the article
"Formal modeling and validation of a power-efficient grouping protocol for WSNs "
at
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When analysing power relations and decision-making processes in developing countries it is evident that 'real politics' does not abide by the formal rules of the game. Rather, there is a considerable element of informality involved, meaning that formal rules are bypassed, evaded or simply disregarded. However, for outsiders, it is exceedingly difficult to come to grips with such informal processes. 
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Arne -
Sabastiano suggested snowball sampling.  If that is appropriate to your needs, then that could give you something quantitative.  However, please note that you will need a relatively large sample size compared to a random sample in cases where populations are known.  The following may be helpful in this regard: 
Best wishes - Jim
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I am looking for studies that manipulate not only the situational frame of social dilemma, like calling the interaction a Competition Game/Wall Street Game or Cooperation Game/Community Game, but that also compare those to a control or baseline. Most studies that I find do not do the comparison with a control. Only recent study I could find is Engel & Rand (2014).
Thanks in advance!
Max Wohlers
Engel, C., & Rand, D. G. (2014). What does “clean” really mean? The implicit framing of decontextualized experiments. Economics Letters, 122(3), 386-389.
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Hi Vikas, 
yes it seems rather interesting that most of the time a comparison to a control is left out. And yes, I am planning to look into that matter!
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I am writing an article on the use of Game theories to determine the outcome of a negotiated agreement. However, as I proceed, it is becoming rather apparent that The elusiveness of the determination of a negotiated outcome, as an inherent feature sorrounding negotiations, makes it unlikely that a simple schematic layout of the disputants options could infact facilitate successful outcome of negotiations, let alone predict the outcome. 
Could someone kindly realign my train of thoughts.
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Hi, Naledi. If the appropiate data exists, outome predictions can indeed be proposed by bargaining models. "Determine", however, is a too strong word.
The original work of Bruce Bueno de Mesquita in ("Political Forcasting: An expected utility model", 1994, Predicting Politics 2002)  and the collective volume by R. Thomson et all, The European Union Decides 1999, as well as my article "Does implicit voting matters", address directly the issue of prediction with formal models.
For discussion of methodology and evaluation of predictions, I suggest you look at Achen's chapter "Evaluating political decision-making models", in The European Union Decides. 
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Is there any solution for the extension of the Bellman optimality Equation for Markov decision problem while the state and action spaces both are uncountable and bounded and compact?
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Good luck with your research project! As you know, dynamic programming is difficult. You may need to use numerical solution methods to solve your DP problem. In that case you may want to look at the book by Judd or the book by Miranda & Fackler.
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Hi, I need articles or research works dedicated to game theory problems with parametric  payoff matrix. For instance, you can see in attached article that a parametric values were added in static Rock–Paper–Scissors game matrix. I need more researches and articles like this. Thanks
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I'm not exactly sure is this what you meant, but I immediately came to think about an evacuation game I've been working with. Here are two articles regarding the game:
The game is played in a spatial setting, and the game matrix an agent has is parametric, with regards to the agents distance to the exit.
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Literature in the energy internet and associated market clearance mechanism dealt with game theory based modelling with standard test grid. Is there any other technique (like GA,ANN) that could be used for the same?
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Dear researcher
You can obtain market clearance price using Linear Programming and the constraints affected a value of  market price can be linearized. For instance, shift factor matrices can be employed to linearize transmission constraints in the electricity market. CVX toolbox in Matlab is very helpful to model this problem. 
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I begin with some general question. Is the normative decision theory in primary form applied to real problems? I can hardly find examples of real payoff matrices among toy examples.
Back to main question. I would like to represent in a form of payoff matrix such a problem: incident commander after arriving at the fire ground has such alternatives: 1. Gathering further information; 2. Evacuating of people; 3. Extinguishing the fire.
Candidates to states of nature: fire will extinguish itself;  people will evacuate thyself. 
How to construct the payoff matrix for this problem. Should be the states of nature composed as a combination of the candidates' values:
State 1: won't extinguish itself, won't evacuate thyself;
State 2: will extinguish itself, won't evacuate thyself;
State 3: won't extinguish itself, will evacuate thyself;
State 4: will extinguish itself, will evacuate thyself;
Let assume that candidates are non mutually exclusive and independent.
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A good book that explains the distinction between normative, descriptive, and prescriptive decision theories is Thinking and deciding by J. Baron
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Can anyone give me articles about roles of these contol mechanisms (internal auditor, external auditor and audit committee).
Thank you
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 You just repeated the same question. The example of a behaviour to describe that I was asking for can be "why bigger firms charge higher fees?", for which I can suggest http://www.jstor.org/stable/2491261. The way you ask your question requires writing a book as a reply. You need to narrow it down to get meaningful answers.
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I am looking for a theoretical economics study that can illustrate a seller's decision when he needs to select one of the two options: he can sell his product to a market with a fixed price (moderate) or a market with a random price (extremely low or high). How can he decide which market to go?
Other than explaining this using a simple risk preference approach, is there any theoretical study that explains determinants of his decision? I would be great if you can provide some suggestions.
Thanks. 
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Thank you for your reply. I am well aware of the literature on expected utility theory and risk preference. What I wanted to ask was whether there is other approach that can explain a seller's decision under uncertainty (e.g., transaction cost economics). 
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I am looking for the methods like ELECTRE IV or MAXIMIN, and for papers where the problem of the criteriaincomparability is considered.
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Maceij
You don't need to create weights for criteria. You can use Shannon's entropy method that gives exact weights based on  information contained in the problem, that is, without subjectivity. Zavadskas has an example of this
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The topic of my thesis is fairness students in financial decision-making. We did an experiment where we fairness surveyed by the dictator game . I mean I need advice on what to put in the practical part . How to handle the data . What statistical methods I could use , I had found that the perception of risk ?
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Hi Stefan,
as Sacha, I would simply propose to employ an analysis, which was already done in similar investigations. So simply check your references, where your theory stems from and do the same. It is of course reasonable to expect the occurance of an effect based on assumptions, methods and analyses of previous studies.
However, if you want detailed advice beyond, you should lay out your design, method and procedure. And... usually chosing a specific statistical analysis should be considered during designing the experiment. ;). This is a presrequesit to determine statistical Power/sample size, and is a matter of scientific reliability. Furthermore, you could otherwise end up with a design on which no statistical test applies (it happened to me in my first-ever-experiment :)).
Best, René
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Let's consider a Generalized Nash Equilibrium Problem (GNEP) ,in which N players play a non-cooprative game with nondisjoint strategy sets. Under the assumption of perfect information game, we could formulate GNEP as Variational Inequalities (VI) problem in order to be able analyzing optimality and existence of the game solutions [1]. Now, I want to reformulate the GNEP under the assumption of imperfect information game as "Differential Variational Inequalities (DVI)" problem. Obviously, taking advantages of "decision dynamics" and "estimation dynamics" are required in imprefect games. How could I do this? And then, how do I solve DVI?
Also, you could find [1] from link below.
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sorry I do not have the expertise to answer this question.
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The topic of my thesis is the perception of economic risk students. We did an experiment where we investigated the perception of risk by lottery games . I mean I need advice on what to put in the practical part . How to handle the data . What statistical methods I could use , I had found that the perception of risk ?
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Hello Otilia,
As I understand, you are looking here to use the experimental game theory. For this you can refer to the studies of  Blomfield (1997); Zimbelman and Waller (1999); King (2002); Fischbacher and Stefani (2007) and Bowlin et al. (2009). Those authors use experimental game theory in audit field.
Attached some references:
Bowlin, K. 2011. Risk-Based Auditing, Strategic Prompts, And Auditor Sensitivity To The Strategic Risk Of Fraud. The Accounting Review, 86, 1231-1253.
Blomfield 1995. Strategic Dependence And Inherent Risk Assessment. The Accounting Review, 70, 71-90.
Zimbelman, M. F. & Waller, W. S. 1999. An Experimental Investigation Of Auditor-Auditee Interaction Under Ambiguities. Journal Of Accounting Research, 135-155.
For example,  Zimbelman and Waller (1999), after collecting data using experiment, they have used Ordinary least squares (OLS) and logistic regressions to analyze the different results. 
Hope that I have answer to your questions, really sorry I am not economist I am accounting researcher and I am interested on using game theory in accouting and tax purposes. 
All the best
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My research background is Operations Research and Social Simulation. More recently I got involved in discussing ways of linking Behavioural Economics models/ideas to Social Simulation. One method that seems to be well suited for this purpose is behavioural game theory. But there are still a few fundamental things I do not understand. Perhaps someone can help me with this.
I was wondering how the outcome of a behavioural game theory experiment helps one to solve concrete problems in the real world. What is the research process one would use? Do I start my investigation with having a concrete problem in mind and think about which game can help me to solve it or do I start my investigation with a game and then think about which concrete problem this could solve or do I just provide the results of a game and let other people find concrete applications in the real world?
Having read recently about the public goods games I was wondering if I can somehow use or link the outcome of such games to build social simulation models of shared houses. Does that make any sense?
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FROM DATA TO THEORY: Augustin Counot developed theory from data and experiment. The supply and demand curve were derived from experiments. Whereas Alfred Marshall working on the same problem 30 years later who explained his approach as:
"(1) Use mathematics as shorthand language, rather than as an engine of inquiry. (2) Keep to them till you have done. (3) Translate into English. (4) Then illustrate by examples that are important in real life (5) Burn the mathematics. (6) If you can't succeed in 4, burn 3. This I do often." See Dimand.
FROM THEORY TO DATA: John F. Nash's approach is to start with theory, i.e. a mathematical model about human interactions. This theory-to-data approach later became the basis of many models in human behaviors, economics, foreign policies, etc. The weakness of this approach is if the theory does not have the data to match, the theory just remain a theory. However, it empirical data supports the theory and the theory gains acceptance and popularity, the approach is equally valid. Nash was award the Nobel Prize in 1994 for his work.
FROM OUTCOME TO THEORY: Most theories of human behavior is to move from data to theory. Through observations, the researcher tries to make a generalization. From the general statement, a mathematical model is built and then subject the model to empirical test. Alfred Marshall seems to have followed this path. So too was Charles Darwin from his observations of the Voyage of the Beagle.
REFERENCES:
[1] Cournot A. (1838) Researches on the Mathematical Principles of the Theory of Wealth
[2] Dimand, Robert W. (2007). "Keynes, IS-LM, and the Marshallian Tradition". History of Political Economy (Duke University Press) 39 (1): 81–95. doi:10.1215/00182702-2006-024
[3] Nash, John (1950) "Equilibrium points in n-person games" Proceedings of the National Academy of Sciences 36(1):48-49.
[4] Nash, John (1951) "Non-Cooperative Games" The Annals of Mathematics 54(2):286-295.
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In the studying of algorithmic game theory I have faced with the proposition ‘A nondegenerate bimatrix game has an odd number of Nash equilibria ’ .
Could anyone introduce me some references for illustrative proof?
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I believe this refers to a result of Wilson in 1971, which shows that *almost all* bimatrix games have finite and odd equilibria.  I am personally not familiar with the proof, but my guess is that it is similar to index theory in dynamical systems, as essentially the existence of a Nash equilibrium reduces to the Brower fixed point theorem.  I've attached some references which are probably more helpful than the original paper.  Hope that helps!
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I want to study the Evolutionary Game Dynamics and its applications on Economics topic?
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I am sorry that I have forgotten  to give you some introductory documents to the U-Mart, although the best introduction is the above cited book:
Artificial Market Experiments with the U-MART (with CD), Springer, 2008.
You have more handy way to know the essentials of the U-Mart. Please see the pamphlet we made. The link is given below.  Uses in education are explained with several examples.
We are planning to publish a new book, again from Springer in this year.
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It is kind of common knowledge in behavioral economics that there is such a thing as the "immediacy effect", i.e. subjects value rewards significantly higher, when they are obtained immediately.
But unfortunately there does not seem to be a paper, which studies this effect (apart from those concentrating on time preferences, which - if present biased - of course also produce a similar effect).
Do you know of experiments where this effect is analysed?
Thanks very much.
Michael
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Delving deeper into the cognitive effects/defects characterized as 1/f noise may provide empirical basis for the "immediacy effect"
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How to find the solution of multiple players Nash game?
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You could take a look at the works:
1) Reasoning about Equilibria in Game-like Concurrent Systems  by Julian Gutierrez, Paul Harrenste in and Michael Wooldridge (http://www.cs.ox.ac.uk/people/julian.gutierrez/web/kr14.pdf)
2) Reasoning About Strategies: On the Model-Checking Problem by Fabio Mogavero, Aniello Murano, Giueseppe Pereli, and Moshe Y. Vardi (http://tocl.acm.org/accepted/mogavero-murano_reasoning.pdf
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Hello every one,
I use ATMS notion to describe my problem and I use label and nogood. I look for a paper which describes an algorithm that calculates these two sets (or one of them). I try to look on internet by nothing.
thanks in advance
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thank you for your help
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Let us modelize a riddle:
We have a finite set of elements E and some subsets A_i.
For the riddle, an unknown element e is chosen in E and the player asks a sequence of questions " is e in A_i ?" An oracle answers yes or no. The goal is to find e.
The strategy of the player is modelized by a binary tree of questions (each node is labeled by a subset A_i with two branches (e is in A_i) or (e is not in A_i)). Notice that A_i can appear several times in the tree. Such a tree is said to be discriminatory if it allows you to find any element of e.
The problem is: build the discriminative tree of minimal height (we can consider the height as an average or the maximal one).
In fact, our goal is to have an algorithm that takes the A_i and builds the decision tree of minimal height.
This problem has probably been investigated for a long time. In which framework ? (data base, game theory, information theory?). If you know anything about this problem, please let me know because I didn't find anything on the web.
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Thanks a lot for your interesting answers. ID3 was the kind of things that I had in mind. The keywords for my question was "decision tree":
- or nice book chapter for a survey on the question  http://www.ise.bgu.ac.il/faculty/liorr/hbchap9.pdf  .
The question that I had in mind was exactly: give an algorithm to build  a decision tree of minimal height . Nevertheless, the problem is NP-hard (Naumov 91 and other references are cited in the book chapter I mentionned) and the book chapter gives an overview of the work in this field.
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Please suggest papers apart from jensen n miller's paper on giffen behavior..
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Jensen, R. T., and Miller, N. H., 2008. Giffen Behavior and Subsistence Consumption. American Economic Review 98, 1553-1577.
Abstract:
This paper provides the first real-world evidence of Giffen behavior, i.e., upward sloping demand. Subsidizing the prices of dietary staples for extremely poor households in two provinces of China, we find strong evidence of Giffen behavior for rice in Hunan, and weaker evidence for wheat in Gansu. The data provide new insight into the consumption behavior of the poor, who act as though maximizing utility subject to subsistence concerns. We find that their elasticity of demand depends significantly, and nonlinearly, on the severity of their poverty. Understanding this heterogeneity is important for the effective design of welfare programs for the poor.
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Are there any researchers who have published about the extensive form of population Game Theory and its applications?
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Thanks Dr. Amie Mittal.
‌But here, what is it mean the population in game?What is the difference between the static and dynamic form in population game? and What  do you know about the applications population game?
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My ant-inspired deceiver robot is supposed to decide on whether or not to leave a track and also the amount of pheromone to deposit in order to confuse the other robot seeking for him. 
-apparently the players are in conflict and it is a non-cooperative game (for now of course, since deception in cooperative situation by convincing the rival do a part of your task in cooperation might be a step forward)
- on the way to extract eternal payoffs (on the basis of which, the robot under deception decides where to go), I use fuzzy inference to cover the uncertainties and have a real-world deception.
also the behavioral strategies for both of the robots are fuzzified throughout an honesty-deception axis (it means the deceiver can sometimes act honestly and also the other robot can sometimes trust what it observes)
- Finally after the decision-making happens, I have modeled it as a zero-sum game, (deception successful: +1 for deceiver and -1 for the other, and vice versa if deception is defeated ), however I'm trying to have a game with fuzzy payoffs.
- I know it is a game with incomplete information from the view of the robot under deception, maybe I can model it as a signaling game.
- I know from the deceiver's point of view, it can be modeled as a kind of resource allocation problem: he must decide on the track and pheromone on the corridors, but the resources here sound unbounded!
-I know the parameters deceiver wants to optimize are: track and pheromone and maybe where to hide, but I doubt about the optimization parameters for the other (maybe where to go to find the deceiver)
-on the basis of what, the players should decide on their behavioral strategy? (act honest/deceitful or act anti-deception/ trust ) ... maybe based on their experience (the game history: the more time you've been deceived, the less you'll trust and also the more time your deception is defeated, the more deceitfully you'll act) .... then I'll face repeated games!
I would be greatly thankful to anyone who helps me with the issue and survive me from this huge pile of vague questions.
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Dear Dr. Edhan,
Many thanks for your interest and valuable help and actually sorry for such a great delay in my reply. 
As far as I've been concerned with the first pages of the attached paper, the game model discussed sounds really interesting to realize a mutual deception while the signaling games which I recently studied about is capable of realizing only a one-sided deception unless regarded from both aspects by changing the roles of the players in each stage!... 
My main problem during this project was indeed the new world of game theory I had set foot on! and unfortunately despite all my efforts to make contacts, because of the special application under study, I was deprived of an expert's help in this field and totally dependent on my own studies, that's why after studying a really huge pile of books and papers I;m now ended in signaling games as a model to try hoping not to fail just like other models tried before!
But the game model you suggested seems much more interesting! and surely I'll try to bring my robots in this environment! 
I'd be most thankful if I'm allowed to keep in touch with you.
Thanks a million,
Maryam Kouzehgar
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Does any one know or point out the method or technique used for the distribution of the coalition cost among the coalition members depending upon their contributions in the coalition. In other words, if a member of the coalition contributes more in the coalition as compared to others then the share of the coalition cost would be less as compared to others? 
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Power vector based method is strong and very intuitive including division of benefits based on the power or strength of the individuals to influence decisions which may consider even breaking away. The paper you can use is as follows:  P Jean-Jacques Herings , Gerard van der Laan , Dolf Talman “The socially stable core in structured transferable utility games”, Games and Economic Behavior, Volume 59, Issue 1, April 2007, Pages 85-104 
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As Venter (1983) has suggested u'(w)=0 for w<0, utility for negative values is constant. A bit different treatment could be u(x)=-u(-x). But how is to calculate risk aversion (R) for situation when wealth value is negative and the agent can be considered to be bankrupt.
Do you agree that I can take R(w)=0 when w<0 since after going broke the agent is indifferent about going even more "broke"?
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hello, Corina,
As I understand you are looking for a study that had empirically measured a CARA coefficient? Right? I didn't see any of those mostly because CRRA is more conventional form of risk aversion function. Regarding CRRA measurements you can take a look at Friend and Blume (1975) the Demand for Risky Assets or Heinemann (2005) Measuring Risk Aversion and the Wealth Effect.
Perhaps, someone else can give a better comments to your question
All the best
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In a one shot game theory, if the action set is convex, but the utility function is a non-convex function on the action set, can it have an equilibrium?
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A game might have at least one equilibrium even if you do not restrict the utility functions (take a look at the Nash's existence theorem). However, if the utility functions are concave, you might guarantee that the game has only one Nash equilibrium.
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Bias, experiments and methods. What is the trend?
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You will find the meaning and explanation of behavioural finance in these articles useful, among others.
Lawrence H. Summers (1986). Does the stock market Rationally Reflect Fundamental Values? Journal of Finance, 41(3):591-601.
Baker M. and Wurgler J. (2013). Behavioural Corporate Finance: An Updated Survey, Handbook of the Economics of Finance, 357-424.
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There are three functions of money. Yes, that is what the books are telling us. But how can something which contains only a "meaning" of something hold any kind of value? My argumenting line is as follows: value is not real, it is human made. It is more a feeling than anything else. And even if we use some kind of matter which is quite stable in its materialized form, the condition of "keeping its value" is totally outside of this stuff. There are the external conditions, the stable condition of expectations of the inhabitants, and more totally external factors until the final one that is if you want to get something in exchange for this "storage," the other part must be there when you want it (which is a condition not connected to the existence of the medium of "storage of value").
So I would say, any storage of value function is only possible as long as a lot of external conditions are stable. Therefore there is really no possible way of saying "this is a storage of value," because everything of "this" points directly to the external conditions, and not to the medium which is used like a storage of value.
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The ability of a currency to store value occurs for both external reasons, which you seem to focus on, and internal reasons that revolve around the currency itself. A simple example - in a period of hyperinflation, caused by the use of seigniorage to finance government operations (printing money) will cause the value of currency to diminish quickly in short periods of time classic examples - Germany, Zimbabwe among many). In such cases people attempt not to hold or use the currency or attempt to exchange it for something else immediately after receiving it exactly because the store of value function has broken down (hyperinflation causes the price level to rise and the value of a currency unit to fall appreciably - holders of the currency see the value of their currency holdings reduced.in terms of what they can exchange it for). What people are willing to exchange the currency for is constantly being eroded in such cases and is a good example of how the store of value function works (or doesn't work in this case) regardless of external issues. This is just one example of where the issue is still relevant.
While I could point you to a lot of texts that discuss this at length a simple search of the internet will unearth a lot of good material. A couple fun examples of the functions of money and bitcoin appear in the NY Times this past Saturday (Mar 1, 2014). See Robert Shiller's "Economic View" on money as a unit of account, and Joe Nocera's Opinion column on bitcoin and its store of value. There have been lots of other discussions like this recently in the press and academic blogs
Nocera:
Shiller:
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I am considering the relation between a player and his agent or agents in definition of the game.
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In game theory there is no formal difference between player and agent. Some authors prefer the term "player" and others may prefer the term "agent". In general, if your audience is formed by game theorists, the term "player" is fine, because it makes clear the kind of decision maker you are referring to. If your audience is not formed by game theorists, the term "agent" may be more appropriate in order to avoid misunderstandings (unless your are talking about actual tabletop games).
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I'm looking for data from prisoner's dilemma experiments in which participants played only one round of the game. A closely related experiment, which I found, is Goeree, Holt and Laury (J Pub Econ 2002) where participants play ten one-shot games without feedback between games (hence, no learning effects).
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Correct
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Any discussion of value is not precise as long there is no precise definition of value and how to measure it or where are the border lines of the value in focus.
One first question of value is: Is there a given absolute value scale - or is it just and only a relative relation of a given value of one part of the economy to the other parts or the total sum.
I strongly would say: It depends.
It depends of one condistion: Is there a measurable definition of "ONE PART OF ECONOMY" yes or no?
My argument is as follows:
The value of one produced part of a given economy is - in the first line - a relative value to the total sum of that given economy.
Which results in the saying that nothing inside of that economy can get a value bigger than 100% of that total value.
The second answer in the second line then is:
If you have a given MEASURABLE DEFINITION of ONE PART OF ECONOMY you end up in a situation where you can measure the economy in real terms - and by going over the total 100% rule back to the percentage of the one given product - you have a direct measurement possible for the true size of ONE PART OF ECONOMY - and therefore an indirect measure of the TRUE VALUE in absolute terms.
Does everybody follow what I mean? I mean, the quantity equation can be bound to a true measurment of real world units of each given economy - if you have a definition for what ONE PART OF ECONOMY is.
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Hi Olaf. I hope you don't mind if I chime back in on this discussion. I confess that I do not follow all of your points on why everything must be viewed in relation to the 100%. I hope my response will not be based on a misinterpretation of your views, but if I am not too far off from understanding the meaning of your question, perhaps I can contribute something positive from an economist's perspective by expanding on some points I made earlier.
Naturally it's important to establish that we are using the word value in the same way. In my mind, there are three broad ways in which this word is commonly used:
(1) Value as a metric - such as weight, heat, speed, monetary value, etc. Here we can quote the specific "value" attributed to that object or substance to express it's relative "size" or degree in terms of that metric, and this value is by definition always relative to a numeraire or prescribed measurable unit (which could itself be a percentage of some defined whole, if those are the units that happen to be useful for a particular task, but can be any arbitrarily defined unit provided the unit of measurement is constant).
(2) Value as a measure of human subjective appreciation of a particular experience of a thing of event. This is also a relative valuation, but one that is ultimately psychologically based. Even though we tend to prescribe value to the objects or events themselves, they don't have any inherent value distinct from their relative personal value to members of a society or market. (For example, do I prefer to take a walk in the park today or instead to work and earn enough income to buy a new tv. Here I weigh the relative value of a leisurely walk to the cumulative satisfaction I would get from the tv, and this relative valuation is not connected to anyone else's relative value, except perhaps through the relative market price of these goods - i.e. if it takes three days of work to afford the tv instead of just one, then I my relative valuation should be different. But I will return to the significance of relative market price and other people's subjective valuations in a moment.)
(3) Values as a set of normative or ethical principles which are used to describe someone's guiding principles for relating to the world. For example, the notion of fairness. I'm not sure it makes sense to refer to this type of value as being relative. One value system might be considered as preferable to another (for example, one policy might result in outcomes deemed to be more fair than another), implying a relative comparison, but this comparison is nevertheless evaluating the relative achievement of absolute "goods" or objectives, which form the core principles or ethical values themselves (i.e. the core principle of something being fair or not).
The notion of value that economists tend to be most concerned about is (2) insofar as they aim to understand human behaviour and how markets work, and given the belief that people's behaviour is largely driven by the desire to maximise this type of value. (People are also motivated by ethical values, and as some branches of economics seek to understand this type of behaviour too, the line between the two notions of value is perhaps not so clear. It also goes without saying that economists are also concerned with normative/ethical values - such as the principles of efficiency, equality, and human welfare - in answering the "why" we want to understand behaviour and markets.)
But economists' analysis of value defined in (2) (let's call it "subjective value") in relation to human behaviour and markets has necessitated some type of metric, which has resulted in a link (1) and (2). The simple idea that the amount of personal/psychological satisfaction that one receives from an experience can be ranked enables us to connect subjective valuation to an ordinal scale (with a numeraire that we can arbitrarily call "utils" or utility). So utility falls entirely under the first category of value, which is not ultimately what we care about, but is intended as a way of talking about or representing the relative rankings people make according to the second definition, the thing we actually care about. And although we can't actually measure utility, economists don't need to in order to understand markets - assumptions about how physical objects enter as an input into this subjective value is sufficient to make predictions about behaviour (which may be good or bad predictions, of course, depending on how good or bad these assumptions are, but this is a whole other topic.) There is no requirement that utility be something measurable in practice, and being ordinal by nature no comparisons of this metric across people is necessary.
Going a bit further, in trying to understand how maximising this subjective value translates into behaviour, we need to know something about relative prices of the inputs into the subjective experiences being compared. At this point we can talk about tradeoffs (or what economists refer to as opportunity costs), which transfer the subjective valuations of entire experiences into well-defined relative values of the goods/commodities that are inputs into these experiences, and start building theories about production, trade, and all types of markets. All this stemming from the simple notion of some artificial metric for subjective value that we call utility.
Now to get back to your main question - how do economists proceed from simple notions of subjective valuations of particular goods, which differ from person to person, to placing a value on the aggregate economy? One way to do this is to employ the notion of market value that I mentioned before. Market value is fairly intuitive, it is links people's subjective valuations together through the notion that in ideal circumstances marginal valuations (the value placed on the marginal unit purchased or consumed) is the same across all individuals participating in the market, and finally it is conceptually linked to market prices. To the extent that market prices reflect market values (but they need not under circumstances I listed before), then it seems natural to value all goods by their market prices and then add them up. This gives us a fairly useful (and practical) way of valuing the entire economy because, say, as more apples are produced, all else equal the recorded increase in the value of the economy is reflected in this increase in goods, which people individually value (and tend to value equally, on the margin.) If the quantity of apples produced stays the same but the price of apples falls because society suddenly values apples less for whatever reason (again, assuming price reflects market value) then, all else equal, the value of the economy falls. Once again, the change in the value of the economy is reflecting changes in human subjective valuations on the margin. All we needed to assume is that human experiences can be ranked and apples are an input into these experiences. We need not know anything about the intensity of these experiences themselves nor know how to measure "utilities".
I would also contend that the numeraire with which we measure the total size or value of the economy is conceptually irrelevant, as long as we are adding up consistently measured relative market values. We could measure the economy as a total number of apples, by expressing the values of all other goods in terms of apples, and easily convert to any other measure by simply dividing by the price (or, in an ideal world, the market value) of that good relative to apples. So if the numeraire is apples, this simply becomes the point of reference for the individual, and links back to the subjective valuation of the individual based on how much they value that marginal apple they ate. (The subjective value of the economy to that person is arguably just sum of all of these marginal values, though now we are getting rather abstract). Money turns out to be a pretty good numeraire because the reference becomes a basket of goods that I consume on a day to day basis - that is, I know roughly how much satisfaction $100 provides to me based on the typical basket I would purchase with that money, and therefore the value of the aggregate economy can just be considered a multiple of equivalent baskets.
So what is still true here is that we start with a concept of relative value and end up with one as well. All values are expressed relative to some numeraire, and although this numeraire should serve as a reference to subjective values in terms of people's experiences, these subjective values are only understood in relative terms as well. But the point is that the valuation of the economy we come up with still has meaning - if it grows it potentially tells us something about how the overall level of satisfaction or value of experience in society is evolving over time (again, making some basic assumptions about goods being inputs into the value of these experiences).
It is true by definition that each part of that aggregate value - the value of each good that is being valued in the economy - is always a percentage of the whole. But I would argue that this assertion amounts to just changing the metric/numeraire. That is, instead of the numeraire being, say, apples or dollars, the unit of account is now "the whole" or "the economy", and so all component values are just being rescaled to be consistent with the new unit. But the relative values themselves don't change. For some types of comparisons, this numeraire, according to which all values are expressed as percentages, is useful. I may want to know how the relative importance of the apple industry in the whole economy has evolved over time, and so I would look at how the share of this industry to the total has changed. But if instead I want to get an idea of how the total size of the economy changes over time, because I believe this is connected to individual subjective valuation and welfare, then clearly I need to measure the total economy in terms of some physical unit.
I should just reiterate the point I made earlier about the appropriateness of "market value" as the concept of value for aggregating up to the total value of the economy. While it may be a convenient notion of value given it's relationship to market price, the latter being something we can observe and practically measure, the concept of market value does leave a lot of things out if what we are really after is some measure of aggregate subjective value. The fact that people would often be willing to pay more for a good than they actually pay suggests that market value underestimates actual total value (and just because I can obtain something free, or almost free, and could consume as much as I could possibly want at that low price, does not mean I didn't value the first unit I consumed very highly). As Monika points out, willingness to pay would be a better representation of total subjective valuation. If we could survey everyone and ask what they would be willing to pay, as a society in terms of some numeraire, to not have the entire lot taken away from them, then this would give a metric for the value of the economy that is more representative of subjective valuations.
Cheers.
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Here is the problem:
1. Alice wants to phone Bob.
2. Alice dials Bob's number and the person at the other end claims to be Bob's son Charles.
3. Bob and Charles have indistinguishable voices, so Alice cannot tell them apart on that basis.
4. Information asymmetry exists because Alice knows Bob well, but knows almost nothing about his son Charles.
5. Now it could be the person at the other end of the line is in fact Bob who is pretending to be Charles (maybe Bob doesn't want to speak with Alice and is rebuffing her).
6. The problem: Is there a question Alice can ask in order know whether the receiver is truly Bob or Charles? Is there a question that can be asked that will catch a bluff for sure? How can information asymmetry be exploited to distinguish Bob and Charles?
(Historical note: I did not think up this question. The originator was the German mathematician Ehrhard Behrends. He actually had a real situation of a strange phone call where he phoned a university colleague in his office. A person picked up the phone who claimed to be the son of the colleague, but the voice sounded exactly like the colleague. After the call was over, Ehrhard wondered if there was a question he could have asked that would make him sure if it was the son or not. There possibly is a solution to this problem, and as you will see it is a very interesting one).
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Dear Derek, this is a difficult question. Here is my $0.02 guess.
Alice : "Hello Bob"
Interlocutor : "That's not Bob, I am his son Charles"
Alice : "Hi Charles. In fact, I wanted to talk to you. I have lost the address you gave me yesterday. Can you give it to me again ?"
Here Alice has introduced a false information in her question because Charles had never talked to her yesterday. If the interlocutor is truly Charles, he will simply say so. On the other hand, if the interlocutor is Bob, he can never be sure of what to respond.
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As described in the papers: "Action Recognition And Prediction For Driver Assistance Systems Using Dynamic Belief Networks" and "Enrichment of Qualitative Beliefs for Reasoning under Uncertainty"
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DBN are a way to use factorisation in complex Markov Chain model.
See :
Murphy, Kevin (2002). Dynamic Bayesian Networks: Representation, Inference and Learning. UC Berkeley, Computer Science Division.
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I'm thinking on corrupted societies: hiring an agent that communicates corruption to citizens can be seen as a signal of honesty.
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Please see this paper. One of my coauthors will present the paper in the Econometric Society conference and the Development conference in New Delhi.http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2166221
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I'm currently researching the dynamic moral hazard problem that arises in a multiple-agent framework - where two agents are in one team, such that production of output in each period is determined by unobservable effort by agents in teams. The principal is tasked with implementing the optimal wage schedule so as to obtain an optimal outcome. My problem is of intractable modelling, with clunky notations due to the number of players involved in the two-period game. Any thoughts on how to model this accurately would be greatly appreciated!
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I studied this theorem:
Theorem
Let σ* be an ESS in a pairwise contest, then σ≠σ* and either
(1) π(σ*,σ*) > π(σ,σ*) , or
(2) π(σ*,σ*) = π(σ,σ*) and π(σ*,σ) > π(σ,σ).
Conversely, if either (1) or (2) holds for each σ≠σ* in a two-player game, then σ* is an ESS in the corresponding population game.
When might the first condition (1) be used? Mostly we use the second condition.
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Might Interest you. Proposed Game theory Conferences at IPE in honour of Prof Shapley & CR Rao’s 92nd Birthday
Second International Conference on Game theory Application to Decisions and Policies (GTADP) and International Conference on Game Theory, Operations Research and their Applications and Workshop on Game theory (GTORA) will be held at IPE in Hyderabad from December 17-22, 2012. These conferences are continuation of Game Theory Conferences which produced an Edited Volume, Conference Souvenir and publishable papers. These conferences will be held consecutively on December 17-18, 2012 (GTADP) and December 20-22, 2012 (GTORA).December 18 will be set aside for an excursion for the participants of both the conferences followed by a morning Game theory Workshop for graduate students and others.
We cordially invite you to set aside 6 days for attending the above two Conferences, but you could chose either one of them. Conferences will provide an open platform to worldwide scholars for presenting research and exchanging ideas of new developments in game theory and applications and honour two distinguish academicians. Announcement will be placed on the Game theory website shortly.
Last year’s Sponsoring Institutions: Institute of Public Enterprise, Hyderabad, CR Rao AIMSCCS, Hyderabad, Central University of Rajasthan, Indian Statistical Institute Chennai, Hyderabad University, and Centre for Economics & Finance, London and we received very good feedback. We hope to get continuing support from the above sponsors and invite you to sponsor the conferences. If you want to be on the National or International Programs please send us your CV showing your ongoing interest in Game theory.
Contact: Prof S Deman for GTADP at s_deman2000@yahoo.co.uk, Tel. 0044 208 4594657, 0091 9983748677 (India), & Mob: 0044 7525857351, & Dr Jayasree, IPE, Mob: 00919848455583.
Prof T. Parthasarthy for (GTORA) at T Parthasarthy <pacha14@yahoo.com, ISI Chennai Centre SETS Campus MGR Knowledge City CIT Campus, Taramani Chennai INDIA600113, Tel: +91-44-6663-2507, Fax +91-44-6663-2507, gtora2012@gmail.com
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More context... Suppose an organisation were responsible for administering a process/system in which research proposals were received to be assessed by a group of experts. The admin organisation is criticised for a process that takes many weeks. How might the quality of decision making be kept high whilst the lead time of the process is reduced to a matter of days?
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Thank you Ricardo! I think I understand... This is a great start for me. I hope to start a project on a similar process that might be improved and provide a case for further learning. I may need to take you up on your offer of further clarification. I really appreciate your help and look forward to interacting with you and the others online more into the future. After all, what is more important than the ability to learn to make better decisions! :-) Kind regards, Robin