Questions related to Agent-Based Simulation
Suppose we have a system designed to deliver services to customers arriving during weekdays. The arrival process is modeled as a Poisson process with an Arrival rate of λ, also we use agent-based modeling with NetLogo to study the behavior of customers. After multiple Observation and replication of the model, the first 8 hours was selected as the warm-up period and the remaining time as the steady-state. If we consider the average length of stay (ALOS) as the crucial output data, how should we handle the initialization bias in this case?
As a workaround, is removing those data sufficient if we take into account the effects of the warm-up period on the ALOS?
Basically I would like to know if the FEM solution obtained by Comsol could be used as input that could guide agents to behave in a certain way in the same common mesh. For example stem cells on a scaffold with specific material properties that undergoes a certain type of deformation. What is the most appropriate ABM Software? Any guidance or tip on the procedure that must be followed in order to interface it with Comsol Multiphysics 4 would be valuable
I'm currently developing my first lateral flow immunoassay and I have come accross some publications like
By definition, Public Good (PG) and Common Pool Resource (CPR) are both non-excludable. The main difference is their rivalry property: PG can be consumed without reducing availability for others, while consuming CPR will decrease the available resources for others. PG has free-riders problem (lack of contributions); CPR has "tragedy of the commons problem" (overuse).
I have 3 questions:
1. So in experimental economics, how do you set up a experiment that distinguishes the differences between two games? For example, if it is a CPR game, will you tell participants that 'the resource is limited and you cannot play anymore when it is depleted'?
2. In a paper by Pahl-Wostl and Ebenhöh (2004), they developed a CPR simulation, in which data is from a PG experiment of Fehr and Gächter (2002). How the data of PGG can be used in CPR? Is there any modification required?
3. The difference between the experiment setup in 2 works above is their utility function. For Fehr and Gächter, the_return = total_investment x 0.4. For Pahl-Wostl and Ebenhöh, the_return = total_investment x 0.6 / 4 = total_investment x 0.15. Is it the difference between experiment's description of CPR and PGG?
- Pahl-Wostl and Ebenhöh (2004) - http://jasss.soc.surrey.ac.uk/7/1/3.html
- Fehr and Gächter (2002) - http://www.nature.com/nature/journal/v415/n6868/full/415137a.html
Some agent-based simulation frameworks support the implementation of Belief–Desire–Intention (BDI) agent models directly or through libraries.
I would like to ask what is the best agent-based simulation framework to implement BDI agents?
Thanks & Regards,
Hi everyone, I have to simulate a container terminal on Anylogic, and the agent that enter in the terminal is truck. Trucks can enter empty, loaded with one container or loaded with two container, so the maximum capacity of the trucks is two containers.
How can I tell the program that they can enter empty, loaded with one or two container randomly? thank in advance
#Anylogic #logistics #TerminalContainer #simulation
I came across papers by Sigglekow, Knudsen, Gavetti, etc and they use agent based simulation to generate NK based complex models. From the few paper that I read, none of them mention the software that they use. So, I am looking for recommendations - as a beginner, what would be the best software to learn to be able to simulate such complex models in strategy?
I am looking for tool/s or game/s that may be actual or simulation of agent-based decisions/behavior to test or model decision making patterns.
I want to calculate reputation and trust based on direct information and witness information in my simulation. I was wondering if anyone has an experience about these two subjects. Or, if you know any samples\ software regarding to these areas let me know.
Thanks in advance,
To describe the individual decision-making of an ABS, is recommended that should include the implementation details of subjects and objects of decisions and the multiple levels of decisions making. Decisions rules and uncertainty could be relevant to the problem rationality and, therefore, necessary for the decision-making system.
The agents are in a simplistic trade environment were an agent can buy a resource from potential customers (having various prices). However, the aim is to train the agent on when to buy (optimizing his payoffs) given the limits of time, energy and competition among other agents.
I would like to have different opinions on how to create a human behavior model for an agent-based simulation, starting from a survey.
In particular, I would like to have more references on how to behavior matrices starting from questions that are asked during the surveying activity.
I am interested in the processes of diffusion and sustainability of innovations and finding the connections between actions that enable and inhibit further adoption beyond the first wave of early adopters of proven elearning innovations in universities?
Is there any precise definition for the agent-based simulation? If a discrete event simulation (DES) is load-driven, i.e., decisions are made from a load (e.g., product, customer, etc.) prospective, can we consider it as agent-based?
There is some paper suggest that DES and agent-based simulation are separate categories. Why?
Intelligent agents are one of the most promising future emerging fields. The more intelligent they become the more useful they are ! However, intelligent agents without ethical behaviours may turn out to dramatic consequences. How can we define (unformally and formally) an "unethical intelligent agent" in a cooperative multi agent environment ?
I just began using the platform Janus for the development of MAS and it seems interesting. Can the users of this platform give us their feedback about it?
I am writing a computer program that implements an abstract social network of inter-communicating individuals (so a multiple agent system) and I want to be able to compute for each agent in the network of computational agents its individual POWER. I mean actual power, not e.g. power attributed by reputation or constitution. Thus does the mayor of the city of Metropolis have more or less power than the person about to detonate a bomb that will collapse a dam and flood the city? In the UK does the Prime Minister David Cameron have more or less power than Queen Elizabeth or Ian Hislop, editor of the famous satirical magazine Private Eye? By how much?
TO CLARIFY, although the suggestive examples I have given involve human beings [OK, maybe there is some slight doubt about Ian Hislop...] I am looking for (and not yet finding) an ALGORITHMIC means of calculating the "size" of some dynamic attribute reasonably called "power" for a COMPUTATIONAL agent that is a member of a dynamic network of COMPUTATIONAL agents.within a computer. All help much appreciated and duly acknowledged in any consequent publication(s)!
My research is related to innovation processes. Currently I'm studying the process by which startups develop while residing within the environment of a business incubator. I am developing a model that I would like to test using agent-based simulation, but my previous experience in simulation programming goes too far back to be useful. Anybody out there with updated skills on agent-based simulation programming - using AnyLogic or any other tool?
Apart from early models of Sugarscape (local market), hash and beans (by Tesfatsion, incomplete), Litghttower (at EURACE project, also incomplete), and "A Generic Framework for a Combined Agent-based Market and Production Model" by Straatman et. al. What other microeconomic models of markets (goods, land and labor) are there? I have seen some of labor, a lot spatially focused, but not a single one that reproduces basic models.
Note that there are a lot of macroeconomic models, especially of financial markets. That is not what I am searching for. I want a detailed, step-by-step design of consumers, labor, land market that I can build upon.
Computer simulation of biological evolution are largely determined by the objective.
What is the evolution searching for? Does it try to increase the biomass of the system? Does it try to increase the complexity of biological structures? Nothing at all? Just follow its own rules. And if so, are these rules the only possible or are they just contingent?
I am modelling a repeated Public Goods Game using Agent Based Modelling, and thinking of a scenario where one player can skip rounds. In a skipped round, that player will not receive any benefit (and of course not use any resource and not contribute as well). Do you know any works on a scenario similar to this situation?
Im currently working on evaluating ABMS Toolkits for Complex social systems. I wish to know the key components that form the evaluation metrics for ABMS Toolkits.
Alternatively you can use some simple methods. For example you can rank variables based on the utility. Is that true? Sorry if the question seems simple for some of you. I don't have basic knowledge about GA. I just tried to solve an optimization problem in my agent-based model and couldn't figure out why most researchers use GA when alternatively they can have a true answers with simple and traditional methods. For example, in my model I can calculate the utility with all the variable combinations and choose the best result. Is there anything in GA that I cannot see?
Comparison between Multi-agent system platform development.
Is there difference between agent-based modeling platform and multi-agent modeling platform?
Which multi-agent platform is suitable for system of systems modeling?
I am interested in better understanding Non-Player Character (NPC) design in games in order to apply the ideas to social and socio-economic agent-based simulation. I was wondering if there are any object oriented design patterns that are commonly used for the design of NPCs. I am currently using hierarchical finite state machines for defining my agents. As an example one pattern I came across is the actor-role design pattern which seems to be quite useful for my purpose.
the DGS is an adaptation of Holland's Learning Classifier System with Tagged Urns and some additional structure. I'm interested in using it to model socio-technical systems related to information security, privacy, confidentiality, homeland defense, etc. Please share references to published papers or working papers, if possible. I will be coding in Mathematica for prototype, then in Java (or maybe Python) for production.
To initiate the debate, I would like to share with you my views on the question I expressed during a recent TEDx Talk. Simply follow the link: http://www.youtube.com/watch?v=qNF4SgHxKVQ&feature=share&list=PLsRNoUx8w3rNYPACQ4oxdeAcq8mjtpaFP
Controlled laboratory experiments are used (i) to explore individual behavior and (ii) to test theories about individual behavior. A lot of anomalies (endowment effect, context dependence, influence of irrelevant alternatives or framing) are found, not to mention non-material incentives and social preferences. In most agent-based macro-model, the focus is on fluctuations at the macro-level (cyclical behavior of prices, wage-profit-cycles, wealth distribution in econophysics models) which emerge from individual interactions governed by simple rules of thumb. I would like to know more about how the empirical insights from behavioral economics can be taken into account for modeling the behavior of individual agents in agent-based macro-models. Given the variety and complexity of individual behavior found in controlled laboratory experiments, how should the individual behavior of agents be modeled?
I am looking for examples where multi-agent system frameworks (software agent templates) have been used to define the agents of social simulation models.
To give you an example of what I am looking for here is a presentation that I recently gave to my colleagues from the NIBS Network (mainly Economists):
Many thanks to everyone who answered so far :).
I’m involved in a research project looking for different simulation tools for logistic management (in particular infrastructural resource dislocation “optimization”) in military environment.
We are attempting to develop a novel agent-based simulation modelling framework based on principles adopted from software engineering (object oriented analysis and design) to help studying the behaviour of elephants (or any other types of animals) in captivity.
Unlike current models that use an agent based approach for defining the agents and their interactions we want to use UML (use case diagrams, sequence diagrams, class diagrams, and state machine diagrams) for defining our agents and their interaction. But we also want to embed some theoretical knowledge about animal behaviour in our agent definitions. So in the end it will be a mixture between software agents and social simulation agents usually used in the field.
To give you an idea what I am talking about here is a link to a presentation I recently gave to some of my colleagues from the economics department. Although it does not feature animal behaviour the problem we are approaching is similar to that described above – trying out a novel approach to defining agents in a field where UML is relatively unknown.
Do you have any tips for us? Any references we should look at? Any similar projects you know of?
These last years, I have developed many models to tackle real problems, but until now none of them have been used in real situations by decision-makers.
I am curious to know if some of you have heard about examples of agent-based models that are actually used by decision-makers (city-planners, environmental health and safety manager, etc.) and not only by researchers/modelers.
I am working in Computer Science. Here, we commonly use the Unified Modeling Language (UML) for software engineering project (mainly for problem analysis and design). I am surprised it is not more commonly used in Economics or Social Science Agent-Based Modelling.
My questions are:
(1) Why is UML not used more frequently in those fields?
(2) Can we use the UML instead of (or besides) equations to describe (better conceptualise) agent based models in those fields?
(3) Are there any (obvious) rules to translate equations into agents?
I am currently working on evacuation of people facing natural hazards (more especially volcanic hazards and tsunamis). In my fieldwork (Indonesia), people combine walking/motorcycles/trucks to be evacuated. Models such as SIMWALK/Evacuation Root Tools/Route Finder do not fit with this kind of context.
We have written (what we think is) a high quality article in the field of Systems Biology with the title "Comparing Stochastic Differential Equations and Agent-Based Simulation for Studying Early-Stage Cancer" and we are looking for a high quality outlet in the field of Systems Biology or a related field. We have previously published an article in BMC Bioinformatics (Impact Factor 3.03) and we aim to publish this paper in a journal with a higher impact factor. Do you have any suggestions?
The consumer should be able to buy only one good, choosing between the one provided by the various companies. The parameters that I want to consider are: the price, the company's visibility in the market, the quality of the product and the quality perceived by the consumer.
I would be interested by references to papers dealing with "agile modeling" for complex systems simulation (esp. agent-based simulation). Although I'm aware of methodological proposals that more or less "import" or mimic this concept from software engineering, I've actually found very few papers about real applications, or software environments that can enable a continuous loop between modeling and simulation, allow an interactive design of models through the interaction of modelers with a simulation, etc.
What is a suitable ABM framework for learning? That is, something where you can quickly get up to speed and play around with it, to get a feel for how ABM works.
It has to be suited for biological simulations, since that is what I would like to use it for in the end.
I have seen about Flame, Breve, Spade, MASON, Swarm etc, but it is hard to know in beforehand what it is like to work in the respective tools, what is the learning curve etc.
Has anyone done any work in this area? I only found this so far:
Sharpanskykh, A and Stroeve, S H (2011) An agent-based approach for structured modeling, analysis and improvement of safety culture. Computational and Mathematical Organization Theory, 17(1), 77-117. Any other suggestions?
Conference Paper Construction engineering and project management II: agent-ba...
For a lecture, I'm looking for well-documented systems or questions, in any scientific domain, that could be well represented using agent-based models and lead to the design of "mid-size" models. By "mid-size", I mean something between the "small-size" toy models found in the NetLogo library, for instance, and the large ABMs that take months to calibrate and analyze. A student would ideally be able to read the paper(s) describing the system and the associated question(s), and design then code a possible model in 2-3 weeks of work. Any suggestions? A link to the corresponding literature would also be much appreciated. Thanks in advance!