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automata, formal languages, computation, complexity, Turing machine, recursive functions, and beyond ...
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Sorry I put twice the same link: Here is the second link : https://cla.tcs.uj.edu.pl/
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Most of the hybrid automata papers target formal verification of the systems. I am looking for papers that are solving optimal response problems that propose optimal control in power systems under the cyber compromise.
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TABOR: A Graphical Model-based Approach for Anomaly Detection in Industrial Control Systems
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Just like FSM, why pushdown automata not used in sequential logic design.
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Mirzakhmet Syzdykov
thank you sir
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I am working on formal specifications expressed as classical finite-state automata with atomic events. I want to test my work on multiple specifications. Do you know of any archive or repository that contains many (preferably real-world) finite-state automata I could use as examples? I don't care about the format they are expressed in, as long as it is machine-readable.
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The Automata Wiki from Radboud University (Nijmegen, NL) provides a publicly available set of benchmarks of state machines that model real protocols and embedded systems.
The wiki is available at https://automata.cs.ru.nl/
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The multi-analysis modeling of a complex system is the act of building a family of models which allows to cover a large spectrum of analysis methods (such as simulation, formal methods, enactment…) that can be performed to derive various properties of this system. The High-Level Language for Systems Specification (HiLLS) has recently been introduced as a graphical language for discrete event simulation, with potential for other types of analysis, like enactment for rapid system prototyping. HiLLS defines an automata language that also opens the way to formal verification.
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The first ever formal model or can say a high level language for system specification is Transition System in paper "Formal Verification of Parallel Programs" written by Robert M. Keller Princeton University 1976. . This model was proposed to formally specify parallel programs. Many of the models emerged after it such as Automata Theory, Timed Automata, Hybrid Automata, Model Checking tools specific languages are based on the original labeled transition system (LTS). The new languages like HiLLS or Business Process Model and Notation from Object Management Group and many others are basically evolved from early LTS.
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I want answer for that question
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Aisha salim Al-Mamari From the beginning of programming languages and compiler construction, lexical analysis was a very important function. In particular for small languages/computers, something like 80% of processing time would be spent in lexical analysis based on analysis Don Knuth performed in the 1960s.
A typical construction involved the lexer operating quickly on character streams and providing tokens to the parser, which worked on higher-order structure, via streaming (including co-routine coupling). Lexers tend to run in linear time on the text stream, with only minor backup of the parsing point. They are essentially finite-state machines, although there may be a little bit of additional context-free detection.
Although top-down object-oriented parsing is typical now, early parsers (and languages) were often adaptations of precedence grammars, which can be discovered mechanically, are parsed "bottom-up" as the tokenized input stream is delivered but are often hand-crafted because of the need to graft semantic aspects into the procedures and also certain parsing cases. The advantage was that the parsing at this level is also nearly-linear in terms of the tokens, there are almost no backup conditions, and the generation of code can also be near-linear (in what Alan Perlis and colleagues called mindelay operation: minimum delay from scan to do), even today a nice feature for scripting languages and one that does not require intricate storage structures, lifetime management, and object construction.
If you look at language implementations for languages like Python and even Java, you can see the separation in that the default "compiled output" is either a post-lexical tokenization of the original code or is a simple compilation to a pseudo-machine language that is stack and procedure-oriented.
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NOTE This topic/question is purely mathematical, but potentially with some interesting relevance to multi-agent systems in the AI sense.
Suppose, for example, I want a network that once started will run indefinitely, always visiting all of its states before repetition. What is (1) a sufficient condition and (2) a necessary condition for this property?
NOTE For the precise definition of a Finite State Automaton (aka Finite State Machine) see any relevant textbook or the Wikipedia article.
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Some further thinking behind my question:
If the well-known “consensus” problem is formulated as getting from any particular set of FSA initial states to the right “consensual” (i.e. all agree) terminal collective decision, then I am confident that the implicit “lookup” table can be implemented/computed even if the computation has to be distributed over many FSMs -- just because any finite computation can be performed on an FSA provided it’s within its size/speed limits. Of course, signals and states have to be suitably and consistently interpreted as part of the network design. But is this viewpoint misconceived? If it's OK, where can I read about it? It must already have been fully worked out?
Another and possibly more interesting question is: can there be consistent Interpretations of signals as sensory input and action output leading to a consistent interpretation that there is a virtual SPATIAL reality SHARED by a subset of the FSA?
Regards
Jim
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There is a way to model computer networks (in terms of latency, bandwidth, packet size, etc.) through (stochastic?temporized?) automata? If I look for networked automata, I only find automata about "local" network of interacting components (e.g., cells)
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An interesting question. I am glad that interesting reflections, responses and conclusions have emerged that may be an inspiration to continue research in this area. Therefore, I am still reading the answers, following the interesting discussion. Best wishes
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In simple self-replicating machines (exclusive of developmental automata), the structure of the description (machine genome) is very simple. For the von Neumann model, the description is organised in a row major/column minor (or the reverse) order, and is clearly a blueprint. Biological genomes are seen as being strictly not of a blueprint nature but, it is clearly the case that whatever the architecture of the biological genome, it must be manipulable by the cell; the genome is, after all, totally inert.
So, the question pertains to all characters of biological genome architecture, and their delineation. Also, this question has strong potential for elucidating semiotic features of genome architecture.
The kind assistance of other researchers will certainly find value in the theory of developmental automata.
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I can not help you because I do not work in this research orientation
Sorry
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Please recommend recent papers on the applications of fuzzy languages
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Dear Alelsandr,
I suggest you to see links and attached files in yopic.
-Journal of Intelligent & Fuzzy Systems - Volume 34, issue 1 - Journals ...
-Fuzzy Automata and Languages: Theory and Applications ...
-Myhill–Nerode type theory for fuzzy languages and automata ...
-Fuzzy automata and languages : theory and applications in ...
-application of fuzzy languages to pattern recognition - Emerald Insight
-Applications of fuzzy languages to intelligent information retrieval ...
Best regards
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Learning automata are elements designed to beincorporated in a plausible and indefinite
environment. This machine performs some finite operations. Each learning automata has a vector of
probabilities and the vector illustrates the probability with which an operation is done and the total sum of
the entries equal one.
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Is there any method to find out the root node in a directed switching graph whose topology guarantees a spanning tree at any moment?
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You could just compute the difference of the set of nodes and the set of children.
I attached a little proof-of-concept script (python3, ts=8, noexpandtab) that is not optimized but it would be easy to optimize it.(You can check all the stuff while you walk the graph).
Note about the script:
The node ``n7`` is the root element, the graph is a symmetric binary tree, but it would be possible to use the same algorithm with any number of children.
The only element in a tree that has no parent is the root, therefore all nodes that are children cannot be the root.
Aside: A graph with multiple "root-alike" nodes could be handled the same.
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I am working on a project where a routing protocol is developed to choose the best route to deliver emergency alerts using Learning Automata(LA). LA should be implemented in NODES. Am working using NS2 Simulator.
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If you are writing complete new code for your routing protocol then you must implement your LA based next node selection technique in Routing Agent which is responsible for selecting forwarding node in NS-2 based implementation of a routing protocol. If you are going to integrate you LA based next node selection technique in any existing routing protocol already implemented in NS-2 then you must implement your LA approach in Routing Agent of the existing routing protocol.  Routing Agent is is generally implemented as a function in a Routing class. It can be also implemented as a class also, It depends on your coding style. 
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How do we represent the transition function of fuzzy multiset automata similar to fuzzy automata?
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I suggest you tu use the graphviz software :
Regards
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I am interested in work on robots that can interact with children but are not telemedicine. I'm especially interested in social robots that can talk or understand human languae
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You can use humanoid robots as a tool that can intact with children easily, it is like a human being and also can talk and also listen if it is programmed well. Now days a wide researches have been devoted to the use of this kind of robots to health care. One interesting topic is using humanoid ones in helping autistic kids. Some commercial robots have been used recently that look interesting for kids. Some scientific surveys have been done to show the research improvement and also achievements.
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I read the following example in one of my professors notes.
1) we have a SLR(1) Grammar G as following. we use SLR(1) parser generator and generate a parse table S for G. we use LALR(1) parser generator and generate a parse table L for G.
S->AB
A->dAa
A-> lambda (lambda is a string with length=0)
B->aAb
Solution: the number of elements with R (reduce) in S is more than L.
but in one site I read:
2) Suppose T1, T2 is created with SLR(1) and LALR(1) for Grammar G. if G be a SLR(1) Grammar which of the following is TRUE?
a) T1 and T2 has not any difference.
b) total Number of non-error entries in T1 is lower than T2
c) total Number of error entries in T1 is lower than T2
Solution:
The LALR(1) algorithm generates exactly the same states as the SLR(1) algorithm, but it can generate different actions; it is capable of resolving more conflicts than the SLR(1) algorithm. However, if the grammar is SLR(1), both algorithms will produce exactly the same machine (a is right).
any one could describe for me which of them is true?
EDIT: infact my question is why for a given SLR(1) Grammar, the parse table of LALAR(1) and SLR(1) is exactly the same, (error and non-error entries are equal and number of reduce is equal) but for the above grammar, the number of Reduced in S is more than L.
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Perhaps my tutorial on compiling theory might help you:
In particular, take a look at the syntax section.
If you want to do experiments yourself, our jaccie tool plus additional documentation can be found at:
Happy experimenting!
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I am working on modelling the interaction between land-use changes and transport. I am using Metronamica which is a cellular automata based modelling package. One of the things I have come across from my reading, is that CA is not able to handle socio-economic variables. The problem is, in my case socioeconomic factors are very important drivers of urban change. Any suggestions on how I can overcome this?
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Hello Thamuka Moyo,
Urban Change Processes
For the evaluation of operational urban models, the urban change processes to be modelled are identified. Eight types of major urban subsystem are distinguished. They are ordered by the speed by which they change, from slow to fast processes:
- Very slow change: networks, land use. Urban transport, communications and utility networks are the most permanent elements of the physical structure of cities. Large infrastructure projects require a decade or more, and once in place, are rarely abandoned. The land use distribution is equally stable; it changes only incrementally.
- Slow changes: workplaces, housing. Buildings have a life-span of up to one hundred years and take several years from planning to completion. Workplaces(non-residential buildings) such as factories, warehouses, shopping centres or offices, theatres or universities exist much longer than the firms or institutions that occupy them, just as housing exists longer than the house-holds that live in it.
- Fast change: employment, population. Firms are established or closed down, expanded or re-located; this creates new jobs or makes workers redundant and so affects employment. House-holds are created, grow or decline and eventually are dissolved, and in each stage in their life cycle adjust their location and motorisation to their changing needs; this determines the distribution of population and car ownership.
- Immediate change: goods transport, travel. The location of human activities in space gives rise to a demand for spatial interaction in the form of goods transport and travel. These inter-actions are the most flexible phenomena of spatial urban development; they can adjust in minutes or hours to changes in congestion or fluctuations in demand, though in reality adjustment may be retarded by habits, obligations or subscriptions.
There is a ninth subsystem, the urban environment. Its temporal behaviour is more complex. The direct impacts of human activities, such as transport noise and air pollution are immediate; other effects such as water or soil contamination build up incrementally over time, and still others such as long-term climate effects are so slow that they are hardly observable. All other eight sub-systems affect the environment by energy and space consumption, air pollution and noise emission, whereas only locational choices of housing investors and households, firms and workers are co-determined by environmental quality, or lack of it. All nine subsystems are partly market-driven and partly subject to policy regulation.
In the 1950s first efforts were made in the USA to study the interrelationship between trans-port and the spatial development of cities systematically. Hansen (1959) demonstrated for Washington, DC that locations with good accessibility had a higher chance of being developed, and at a higher density, than remote locations ("How accessibility shapes land use").
The recognition that trip and location decisions co-determine each other and that therefore transport and land use planning needed to be co-ordinated, quickly spread among American planners, and the 'land-use transport feedback cycle' became a commonplace in the American planning literature. The set of relationships implied by this term can be briefly summarised as follows:
Figure 1. The 'land-use transport feedback cycle'.
- The distribution of land uses, such as residential, industrial or commercial, over the urban area determines the locations of human activities such as living, working, shopping, education or leisure. - The distribution of human activities in space requires spatial interactions or trips in the transport system to overcome the distance between the locations of activities.
- The distribution of infrastructure in the transport system creates opportunities for spatial interactions and can be measured as accessibility.
- The distribution of accessibility in space co-determines location decisions and so results in changes of the land use system.
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The Chomsky hierarchy is a guideline on language's expressive power. The linear feedback shift register is a very interesting "element" to the structure of a language and there is a large base of theoretical literature on the subject.
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Thank you for your response.
Is at level 2 (context-free) a machine capable of generating LFSR (for example that implements a Berlekamp-Massey algorithm) ?