Examine individual changes

'[[Image:IntelligentAgent-SimpleReflex.png|thumb|right|Simple reflex agent]] [[Image:IntelligentAgent-Learning.png|thumb|right|Learning agent]] A '''multi-agent system''' ('''MAS''') is a system composed of multiple interacting [[intelligent agent]]s within an environment. Multi-agent systems can be used to solve problems that are difficult or impossible for an individual agent or a [[monolithic system]] to solve. Intelligence may include some [[Scientific method|method]]ic, [[Function (computer science)|functional]], [[Algorithm|procedural]] or [[algorithm]]ic [[search algorithm|search]], [[finding|find]] and [[computer data processing|process]]ing approach. Topics where multi-agent systems research may deliver an appropriate approach include online trading,<ref>{{cite journal |first1=Alex |last1=Rogers |first2=E. |last2=David |first3=J. |last3=Schiff |first4=N.R. |last4=Jennings |url=http://eprints.ecs.soton.ac.uk/12716/ |title=The Effects of Proxy Bidding and Minimum Bid Increments within eBay Auctions |journal=ACM Transactions on the Web |year=2007}}</ref> disaster response,<ref>{{cite journal |first1=Nathan |last1=Schurr |first2=Janusz |last2=Marecki |first3=Milind |last3=Tambe |first4=Paul |last4=Scerri | first5=Nikhil |last5=Kasinadhuni |first6=J.P. |last6=Lewis |url=http://teamcore.usc.edu/papers/2005/SS105SchurrN.pdf |format=PDF |title=The Future of Disaster Response: Humans Working with Multiagent Teams using DEFACTO |year=2005}}</ref> and modelling social structures.<ref>{{cite journal |first1=Ron |last1=Sun|authorlink1=Ron Sun |first2=Isaac |last2=Naveh |url=http://jasss.soc.surrey.ac.uk/7/3/5.html |title=Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model |journal=Journal of Artificial Societies and Social Simulation}}</ref> == Concept == Multi-agent systems consist of agents and their environment. Typically multi-agent systems research refers to [[software agent]]s. However, the agents in a multi-agent system could equally well be robots,<ref>{{cite journal |last=Kaminka |first=G. A. |url=http://www.cs.biu.ac.il/~galk/Publications/b2hd-agentlink04.html |title=Robots are Agents, Too!] |journal=AgentLink News |pages=16–17 |month=December |year=2004}}</ref> humans or human teams. A multi-agent system may contain combined human-agent teams. Agents can be divided into different types: * Very simple like: '''passive agents'''<ref name=yoann2010>{{citation |first1=Yoann |last1=Kubera |first2=Philippe |last2=Mathieu |first3=Sébastien |last3=Picault |url=http://www.lifl.fr/SMAC/publications/pdf/aamas2010-everything.pdf |format=PDF |title=Everything can be Agent! |journal=Proceedings of the ninth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'2010) |pages=1547–1548 |year=2010 |location=Toronto, Canada}}</ref> or agent without goals (like obstacle, apple or key in any simple simulation) * '''Active agents'''<ref name=yoann2010/> with simple goals (like birds in flocking, or wolf&ndash;sheep in [[Lotka–Volterra|prey-predator model]]) * Or very complex agents (like cognitive agent, which has a lot of complex calculations) Environment also can be divided into: * Virtual Environment * Discrete Environment * Continuous Environment Agent environments can be organized according to various properties like: accessibility (depending on if it is possible to gather complete information about the environment), determinism (if an action performed in the environment causes a definite effect), dynamics (how many entities influence the environment in the moment), discreteness (whether the number of possible actions in the environment is finite), episodicity (whether agent actions in certain time periods influence other periods),<ref>{{Russell Norvig 2003}}</ref> and dimensionality (whether spatial characteristics are important factors of the environment and the agent considers space in its decision making).<ref name="Salamon2011">{{cite book | last1 = Salamon | first1 = Tomas | title = Design of Agent-Based Models | location = Repin | publisher = Bruckner Publishing | year= 2011 | page = 22 | isbn = 978-80-904661-1-1 | url=http://www.designofagentbasedmodels.info/}}</ref> === Characteristics === The agents in a multi-agent system have several important characteristics:<ref>{{cite book |first=Michael |last=Wooldridge |title=An Introduction to MultiAgent Systems |publisher=[[John Wiley & Sons]] |year=2002 |pages=366 |isbn=0-471-49691-X}}</ref> * '''Autonomy''': the agents are at least partially [[Autonomous agent|autonomous]] * '''Local views''': no agent has a full global view of the system, or the system is too complex for an agent to make practical use of such knowledge * '''Decentralization''': there is no designated controlling agent (or the system is effectively reduced to a monolithic system)<ref>{{cite journal |first1=Liviu |last1=Panait |first2=Sean |last2=Luke |url=http://cs.gmu.edu/~eclab/papers/panait05cooperative.pdf|format=PDF |title=Cooperative Multi-Agent Learning: The State of the Art |journal=Autonomous Agents and Multi-Agent Systems |volume=11 |issue=3 |pages=387–434 |year=2005}}</ref> === Self-organization and self-steering === Multi-agent systems can manifest [[self-organization]] as well as [[self-steering]] and other [[control theory|control paradigms]] and related complex behaviors even when the individual strategies of all their agents are simple. When agents can share knowledge using any agreed language, within the constraints of the system's communication protocol, the approach may lead to a common improvement. Example languages are [[KQML|Knowledge Query Manipulation Language]] (KQML) or [[Agent Communication Language|FIPA's Agent Communication Language]] (ACL). === Systems paradigms === Many MAS systems are implemented in computer simulations, stepping the system through discrete "time steps". The MAS components communicate typically using a weighted request matrix, e.g. Speed-VERY_IMPORTANT: min=45&nbsp;mph, Path length-MEDIUM_IMPORTANCE: max=60 expectedMax=40, Max-Weight-UNIMPORTANT Contract Priority-REGULAR and a weighted response matrix, e.g. Speed-min:50 but only if weather sunny, Path length:25 for sunny / 46 for rainy Contract Priority-REGULAR note - ambulance will override this priority and you'll have to wait A challenge-response-contract scheme is common in MAS systems, where First a '''"Who can?"''' question is distributed. Only the relevant components respond: '''"I can, at this price"'''. Finally, a contract is set up, usually in several more short communication steps between sides, also considering other components, evolving "contracts", and the restriction sets of the component algorithms. Another paradigm commonly used with MAS systems is the pheromone, where components "leave" information for other components "next in line" or "in the vicinity". These "pheromones" may "evaporate" with time, that is their values may decrease (or increase) with time. === Properties === MAS systems, also referred to as "self-organized systems", tend to find the best solution for their problems "without intervention". There is high similarity here to physical phenomena, such as energy minimizing, where physical objects tend to reach the lowest energy possible, within the physical constrained world. For example: many of the cars entering a metropolis in the morning, will be available for leaving that same metropolis in the evening. The main feature which is achieved when developing multi-agent systems, if they work, is flexibility, since a multi-agent system can be added to, modified and reconstructed, without the need for detailed rewriting of the application. These systems also tend to be rapidly self-recovering and failure proof, usually due to the heavy redundancy of components and the self managed features, referred to, above. == The study of multi-agent systems == The study of multi-agent systems is "concerned with the development and analysis of sophisticated [[artificial intelligence|AI]] problem-solving and control architectures for both single-agent and multiple-agent systems."<ref>{{cite web |url=http://mas.cs.umass.edu/ |title=The Multi-Agent Systems Lab |publisher=[[University of Massachusetts Amherst]] |accessdate=Oct 16, 2009}}</ref> Topics of research in MAS include: * agent-oriented software engineering * beliefs, desires, and intentions ([[BDI software agent|BDI]]) * [[Consensus dynamics|cooperation and coordination]] * organization * communication * negotiation * [[cooperative distributed problem solving|distributed problem solving]] * multi-agent learning * scientific communities * dependability and fault-tolerance * robotics <ref>{{cite journal |last1=Ahmed |first1=S. |last2=Karsiti |first2=M.N. |url=http://eprints.utp.edu.my/320/|title=A testbed for control schemes using multi agent nonholonomic robots |work=2007 IEEE International Conference on Electro/Information Technology |year=2007|doi=10.1109/EIT.2007.4374547}}</ref> == Frameworks == While ad hoc multi-agent systems are often created from scratch by researchers and developers, some frameworks have arisen that implement common standards (such as the [[FIPA]] agent system platforms and communication languages). These frameworks save developers time and also aid in the standardization of MAS development. One such developmental framework for robotics is given in <ref>{{cite web |first1=Salman |last1=Ahmed |first2=Mohd N. |last2=Karsiti |first3=Herman |last3=Agustiawan |url=http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.98.879 |title=A development framework for collaborative robots using feedback control|year=2007}}</ref> See [[Comparison of agent-based modeling software]]. == Applications in the real world == {{Expand section|date=December 2008}} <!-- Although MAS is still strictly a research topic, many graphic computer games today are developed using MAS algorithms and MAS frameworks. --> Multi-agent systems are applied in the real world to graphical applications such as computer games. Agent systems have been used in films.<ref>{{cite web |publisher=[[Massive (software)|MASSIVE]] |url=http://www.massivesoftware.com/film.html |title=Film showcase|accessdate=28 April 2012}}</ref> They are also used for coordinated defence systems. Other applications include transportation, logistics,<ref name="compare">{{cite doi|10.1016/j.trc.2009.04.018}}</ref> graphics, [[Geographic information system|GIS]] as well as in many other fields. It is widely being advocated for use in networking and mobile technologies, to achieve automatic and dynamic load balancing, high scalability, and self-healing networks. == See also == {{multicol}} * [[Agent-based model]] (ABM) * [[Comparison of agent-based modeling software]] * [[Agent-Based Computational Economics|Agent-based computational economics (ACE)]] * [[Artificial brain]] * [[Artificial intelligence]] * [[Complex systems]] * [[Distributed artificial intelligence]] * [[Emergence]] * [[Evolutionary computation]] * [[Human-based genetic algorithm]] * [[Intelligent agent]] {{multicol-break}} * [[Knowledge Query and Manipulation Language]] (KQML) * [[Multi-agent planning]] * [[Pattern-oriented modeling]] * [[PlatBox Project]] * [[Scientific Community Metaphor]] * [[Self-organization]] * [[Self-Reconfiguring Modular Robotics]] * [[Simulated reality]] * [[Social simulation]] * [[Software agent]] * [[Swarm Intelligence]] * [[Artificial life framework]] {{multicol-end}} == References == {{reflist|2}} == Further reading == * {{cite book |first=Michael |last=Wooldridge |title=An Introduction to MultiAgent Systems |publisher=[[John Wiley & Sons]] |year=2002 |pages=366 |isbn=0-471-49691-X}} * {{cite book |first1=Yoav |last1=Shoham |first2=Kevin |last2=Leyton-Brown |url=http://www.masfoundations.org Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations |publisher=[[Cambridge University Press]] |year=2008 |pages=496 |isbn=978-0-521-89943-7}} * {{cite journal |last1=Mamadou |first1=Tadiou Koné |last2=Shimazu |first2=A. |last3=Nakajima |first3=T. |title=The State of the Art in Agent Communication Languages (ACL) |journal=Knowledge and Information Systems Journal (KAIS) |publisher=[[Springer-Verlag]] |location=London |volume= 2 |issue=2 |pages=1–26 |month=August |year=2000}} * {{cite journal |first1=Carl |last1=Hewitt |first2=Jeff |last2=Inman |title=DAI Betwixt and Between: From "Intelligent Agents" to Open Systems Science |journal=IEEE Transactions on Systems, Man, and Cybernetics |month=Nov./Dec. |year=1991}} * ''[[Autonomous Agents and Multi-Agent Systems|The Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS)]]'' * {{cite book |editor-first=Gerhard |editor-last=Weiss |title=Multiagent Systems, A Modern Approach to Distributed Artificial Intelligence |publisher=MIT Press |year=1999 |isbn=0-262-23203-0}} * {{cite book |first=Jacques |last=Ferber |title=Multi-Agent Systems: An Introduction to Artificial Intelligence |publisher=Addison-Wesley |year=1999 |isbn=0-201-36048-9}} * {{cite book |last=Sun |first=Ron |authorlink=Ron Sun |year=2006 |title=Cognition and Multi-Agent Interaction |publisher=[[Cambridge University Press]] |url=http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=0-521-83964-5 |isbn=0-521-83964-5}} * {{cite journal |first1=David |last1=Keil |first2=Dina |last2=Goldin |url=http://www.engr.uconn.edu/~dqg/papers/e4mas.pdf |format=PDF |title=Indirect Interaction in Environments for Multiagent Systems |work=Environments for Multiagent Systems II |editor1-first=Danny |editor1-last=Weyns |editor2-first=Van |editor2-last=Parunak |editor3-first=Fabien |editor3-last=Michel |series=LNCS 3830 |publisher=[[Springer Science+Business Media|Springer]] |year=2006}} * ''[http://www.whitestein.com/series Whitestein Series in Software Agent Technologies and Autonomic Computing]'', published by Springer Science+Business Media Group * {{Cite book | last=Salamon | given=Tomas | year=2011 | title=Design of Agent-Based Models : Developing Computer Simulations for a Better Understanding of Social Processes | publisher=Bruckner Publishing | isbn=978-80-904661-1-1 | url=http://www.designofagentbasedmodels.info/ | ref=harv }} * {{Russell Norvig 2003}} ==External links== * [http://www.b-squared.org.ua/enwiki/static/research/example/BZ.html Random Agent-Based Simulations by Borys Biletskyy] – Random agent-base simulations for multi-robot system and Belousov-Zhabotinsky reaction. Java applets available. * [http://cormas.cirad.fr/ CORMAS] (COmmon Resources Multi-Agent System) An open-source [[Software framework|framework]] for Multi-Agent Systems based on [[SmallTalk (langage)|SmallTalk]]. Spatialized, it focuses on issues related to natural resource management and negotiation between stakeholders. * [http://jacamo.sf.net JaCaMo MAS Platform] - An open-source platform for Multi-Agent Systems based on Jason, CArtAgO, and Moise. * [http://www.janus-project.org Janus multiagent Platform] – Holonic multiagent execution platform (free for non-commercial use). * [http://www.hartech.co.il/tech_simulations.html HarTech Technologies] - HarTech Technologies developed a dedicated Distributed Multi Agent System Framework used in both simulation and large scale command and control system. This unique framework called the Generic Blackboard (GBB) provides a development framework for such systems which is domain independent. [http://www.armedforces-int.com/article/gbb-development-framework-for-distributed-multi-agent-systems.html Distributed Multi Agent Framework]. * [http://www.madkit.org/ MadKit] MadKit is a modular and scalable multiagent platform written in Java (GPL/LGPL licence) and built upon the AGR (Agent/Group/Role) organizational model: agents are situated in groups and play roles. MadKit allows high heterogeneity in agent architectures and communication languages, and various customizations. {{Systems}} {{DEFAULTSORT:Multi-Agent System}} [[Category:Multi-agent systems| ]] [[Category:Multi-robot systems]] [[Category:Methods in sociology]]'