Editing Multi-agent system

{{Short description|Built of multiple interacting agents}}
{{Use mdy dates|date=October 2023}}
{{Multi-agent system}}
[[Image:IntelligentAgent-SimpleReflex.png|thumb|right|Simple reflex agent]]
[[Image:IntelligentAgent-Learning.svg|thumb|right|Learning agent]]
A '''multi-agent system''' ('''MAS''' or "self-organized system") is a computerized system composed of multiple interacting [[intelligent agent]]s.<ref>Yoav Shoham, Kevin Leyton-Brown. ''Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations.'' Cambridge University Press, 2009. http://www.masfoundations.org/</ref><ref name="uav">H. Pan; M. Zahmatkesh; F. Rekabi-Bana; F. Arvin; J. Hu "[https://ieeexplore.ieee.org/document/10965835 T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles]" IEEE Transactions on Intelligent Transportation Systems, 2025.</ref> Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a [[monolithic system]] to solve.<ref name="tcas">Hu, J.; Turgut, A.; Lennox, B.; Arvin, F., "[https://ieeexplore.ieee.org/abstract/document/9409965 Robust Formation Coordination of Robot Swarms with Nonlinear Dynamics and Unknown Disturbances: Design and Experiments]" IEEE Transactions on Circuits and Systems II: Express Briefs, 2021.</ref> Intelligence may include [[Scientific method|method]]ic, [[Function (computer science)|functional]], [[Algorithm|procedural]] approaches, [[algorithm]]ic [[search algorithm|search]] or [[reinforcement learning]].<ref>Stefano V. Albrecht, Filippos Christianos, Lukas Schäfer. ''Multi-Agent Reinforcement Learning: Foundations and Modern Approaches.'' MIT Press, 2024. https://www.marl-book.com/</ref> With advancements in [[large language model]]s (LLMs), LLM-based multi-agent systems have emerged as a new area of research, enabling more sophisticated interactions and coordination among agents.<ref name=li2023>{{cite journal | last =Li | first =Guohao | title =Camel: Communicative agents for "mind" exploration of large language model society | journal = Advances in Neural Information Processing Systems | volume = 36 | pages = 51991–52008 | year = 2023 | url = https://proceedings.neurips.cc/paper_files/paper/2023/file/a3621ee907def47c1b952ade25c67698-Paper-Conference.pdf  | arxiv = 2303.17760 | s2cid = 257900712}}</ref>

Despite considerable overlap, a multi-agent system is not always the same as an [[agent-based model]] (ABM).  The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which do not necessarily need to be "intelligent") obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. The terminology of ABM tends to be used more often in the science, and MAS in engineering and technology.<ref name="Niazi-Hussain">{{cite journal |first1=Muaz |last1=Niazi |first2=Amir |last2=Hussain |year=2011 |title=Agent-based Computing from Multi-agent Systems to Agent-Based Models: A Visual Survey |journal=Scientometrics |volume=89 |issue=2 |pages=479–499 |doi=10.1007/s11192-011-0468-9 |url=https://www.researchgate.net/publication/220365334 |format=PDF|arxiv=1708.05872 |hdl=1893/3378 |s2cid=17934527 }}</ref> Applications 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 |volume=1 |issue=2 |pages=9–es |year=2007 |doi=10.1145/1255438.1255441 |citeseerx=10.1.1.65.4539 |s2cid=207163424 |access-date=2008-03-18 |archive-date=2010-04-02 |archive-url=https://web.archive.org/web/20100402101304/http://eprints.ecs.soton.ac.uk/12716/ |url-status=dead }}</ref> disaster response,<ref>{{cite web |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=https://aaai.org/papers/0002-ss05-01-002-the-future-of-disaster-response-humans-working-with-multiagent-teams-using-defacto |title=The Future of Disaster Response: Humans Working with Multiagent Teams using DEFACTO |year=2005 |access-date=8 January 2024 |archive-date=2013-06-03 |archive-url=https://web.archive.org/web/20130603165342/http://teamcore.usc.edu/papers/2005/SS105SchurrN.pdf| url-status=live}}</ref><ref>{{cite book |last1=Genc|first1=Zulkuf  |title=Intelligent Systems for Crisis Management |chapter=Agent-Based Information Infrastructure for Disaster Management |chapter-url=http://www.gdmc.nl/gi4dmdocs/Gi4DM_2012_Genc.pdf |pages=349–355 |date=2013|display-authors=etal|doi=10.1007/978-3-642-33218-0_26 |isbn=978-3-642-33217-3 |series=Lecture Notes in Geoinformation and Cartography }}</ref> target surveillance<ref>{{cite journal |last1=Hu |first1=Junyan |last2=Bhowmick |first2=Parijat|last3=Lanzon |first3=Alexander  |title=Distributed Adaptive Time-Varying Group Formation Tracking for Multiagent Systems With Multiple Leaders on Directed Graphs |journal=IEEE Transactions on Control of Network Systems |date=2020  |volume=7 |pages=140–150 |doi=10.1109/TCNS.2019.2913619 |s2cid=149609966 |doi-access=free }}</ref> and social structure modelling.<ref>{{cite journal |first1=Ron |last1=Sun|author-link1=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|date=30 June 2004}}</ref>

== Concept ==

Multi-agent systems consist of agents and their [[Biophysical environment|environment]]. Typically multi-agent systems research refers to [[software agent]]s. However, the agents in a multi-agent system could equally well be robots, humans or human teams. A multi-agent system may contain combined human-agent teams.

Agents can be divided into types spanning simple to complex. Categories include:
* 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 |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 }}</ref> or "agent without goals" (such as obstacle, apple or key in any simple simulation)
* Active agents<ref name=yoann2010/> with simple goals (like birds in flocking, or wolf–sheep in [[Lotka–Volterra|prey-predator model]])
* Cognitive agents (complex calculations)

Agent environments can be divided into:
* Virtual
* Discrete
* Continuous

Agent environments can also be organized according to properties such as accessibility (whether it is possible to gather complete information about the environment), determinism (whether an action 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> Agent actions are typically mediated via an appropriate middleware. This middleware offers a first-class design abstraction for multi-agent systems, providing means to govern resource access and agent coordination.<ref>{{ cite journal |first1=Danny |last1=Weyns |first2=Amdrea |last2=Omicini |first3=James |last3=Odell |year=2007 |title=Environment as a first-class abstraction in multiagent systems |journal=Autonomous Agents and Multi-Agent Systems |volume=14 |issue=1 |pages=5–30 |doi=10.1007/s10458-006-0012-0 |citeseerx=10.1.1.154.4480 |s2cid=13347050 }}</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=978-0-471-49691-5}}</ref>

* Autonomy: agents at least partially independent, self-aware, [[Autonomous agent|autonomous]]
* Local views: no agent has a full global view, or the system is too complex for an agent to exploit such knowledge
* Decentralization: no agent is designated as controlling (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|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 |doi=10.1007/s10458-005-2631-2|citeseerx=10.1.1.307.6671 |s2cid=19706 }}</ref>

=== Self-organisation and self-direction ===

Multi-agent systems can manifest [[self-organisation]] as well as self-direction and other [[control theory|control paradigms]] and related complex behaviors even when the individual strategies of all their agents are simple.{{citation needed|date=December 2016}} 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]] (ACL).

=== System paradigms ===

Many MAS 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 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 is the "[[pheromone]]", where components leave information for other nearby components. These pheromones may evaporate/concentrate with time, that is their values may decrease (or increase).

=== Properties ===

MAS 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 physically 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 systems also tend to prevent propagation of faults, self-recover and be fault tolerant, mainly due to the redundancy of components.

== Research ==

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]] |access-date=Oct 16, 2009}}</ref> Research topics include:
* agent-oriented software engineering
* beliefs, desires, and intentions ([[BDI software agent|BDI]])
* [[Consensus dynamics|cooperation and coordination]]
* [[distributed constraint optimization]] (DCOPs)
* organization
* communication
* negotiation
* [[cooperative distributed problem solving|distributed problem solving]]
*[[multi-agent learning]]<ref>{{citation|first1=Stefano |last1=Albrecht |first2=Peter |last2=Stone |year=2017 |contribution=Multiagent Learning: Foundations and Recent Trends. Tutorial |title=IJCAI-17 conference |url=http://www.cs.utexas.edu/~larg/ijcai17_tutorial/multiagent_learning.pdf}}</ref>
* [[agent mining]] 
* scientific communities (e.g., on biological flocking, language evolution, and economics)<ref>{{ cite journal | last =Cucker | first =Felipe | author2=Steve Smale | year =2007 | title =The Mathematics of Emergence | journal = Japanese Journal of Mathematics | volume = 2| pages = 197–227| url =http://ttic.uchicago.edu/~smale/papers/math-of-emergence.pdf | access-date = 2008-06-09 | doi =10.1007/s11537-007-0647-x | s2cid =2637067 | author2-link =Stephen Smale }}</ref><ref>{{ cite journal | last =Shen | first =Jackie (Jianhong) | year =2008 | title =Cucker–Smale Flocking under Hierarchical Leadership | journal =SIAM J. Appl. Math. | volume =68 | issue =3 | pages = 694–719| url =http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=SMJMAP000068000003000694000001&idtype=cvips&gifs=yes | access-date = 2008-06-09 | doi =10.1137/060673254 | arxiv =q-bio/0610048| s2cid =14655317 }}
</ref>
* dependability and fault-tolerance
* robotics,<ref>{{citation|last1=Ahmed |first1=S. |pages=459 |last2=Karsiti |first2=M.N. |url=http://eprints.utp.edu.my/320/|title=2007 IEEE International Conference on Electro/Information Technology |year=2007|doi=10.1109/EIT.2007.4374547|contribution=A testbed for control schemes using multi agent nonholonomic robots |isbn=978-1-4244-0940-2 |s2cid=2734931 |url-access=subscription }}</ref> multi-robot systems (MRS), robotic clusters
* multi-agent systems also present possible applications in microrobotics,<ref>{{cite journal |last1=Yang |first1=Lidong |last2=Li |first2=Zhang |year=2021 |title=Motion control in magnetic microrobotics: From individual and multiple robots to swarms |journal=Annual Review of Control, Robotics, and Autonomous Systems |volume=4 |pages=509–534 |doi=10.1146/annurev-control-032720-104318|s2cid=228892228 }}</ref> where the physical interaction between the agents are exploited to perform complex tasks such as manipulation and assembly of passive components.
* language model-based multi-agent systems<ref name=li2023></ref>

== Frameworks ==

Frameworks have emerged that implement common standards (such as the [[Foundation for Intelligent Physical Agents|FIPA]] and [[Object Management Group|OMG]] MASIF standards).<ref>{{Cite web|url=https://www.omg.org/cgi-bin/doc?orbos/97-10-05|title=OMG Document – orbos/97-10-05 (Update of Revised MAF Submission)|website=www.omg.org|access-date=2019-02-19}}</ref> These frameworks e.g. [[Java Agent Development Framework|JADE]], save time and aid in the standardization of MAS development.<ref name=DF_1>{{cite web |first1=Salman |last1=Ahmed  |first2=Mohd N. |last2=Karsiti |first3=Herman |last3=Agustiawan |title=A development framework for collaborative robots using feedback control| url=https://www.researchgate.net/publication/238431442| year=2007| access-date=8 January 2024}}</ref>

Currently though, no standard is actively maintained from FIPA or OMG. Efforts for further development of software agents in industrial context are carried out in [[Institute of Electrical and Electronics Engineers|IEEE]] IES technical committee on Industrial Agents.<ref>{{Cite web|url=https://tcia.ieee-ies.org/|title=IEEE IES Technical Committee on Industrial Agents (TC-IA)|website=tcia.ieee-ies.org|access-date=2019-02-19}}</ref>

With advancements in [[large language model]]s (LLMs) such as [[ChatGPT]], LLM-based multi-agent frameworks, such as [[Apache Camel|CAMEL]],<ref name="camel2023">{{Cite web |title=CAMEL: Finding the Scaling Law of Agents. The first and the best multi-agent framework. |url=https://github.com/camel-ai/camel/ |website=[[GitHub]]}}</ref><ref name="li2023" /> have emerged as a new paradigm for developing multi-agent applications.

== Applications ==<!-- Although MAS is still strictly a research topic, many graphic computer games today are developed using MAS algorithms and MAS frameworks. -->
MAS have not only been applied in academic research, but also in industry.<ref>{{Cite book|title=Industrial agents : emerging applications of software agents in industry|others=Leitão, Paulo,, Karnouskos, Stamatis|isbn=978-0128003411|location=Amsterdam, Netherlands|oclc=905853947|last1 = Leitão|first1 = Paulo|last2 = Karnouskos|first2 = Stamatis|date = 2015-03-26}}</ref> MAS 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|access-date=28 April 2012}}</ref> It is widely advocated for use in networking and mobile technologies, to achieve automatic and dynamic load balancing, high scalability and self-healing networks. They are being used for coordinated defence systems.

Other applications<ref>{{Cite journal|last1=Leitao|first1=Paulo|last2=Karnouskos|first2=Stamatis|last3=Ribeiro|first3=Luis|last4=Lee|first4=Jay|last5=Strasser|first5=Thomas|last6=Colombo|first6=Armando W.|date=2016|title=Smart Agents in Industrial Cyber–Physical Systems|journal=Proceedings of the IEEE|volume=104|issue=5|pages=1086–1101|doi=10.1109/JPROC.2016.2521931|s2cid=579475|issn=0018-9219|url=http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-128744|hdl=10198/15438|hdl-access=free}}</ref> include [[transportation]],<ref name="surtrac2012b">Xiao-Feng Xie, S. Smith, G. Barlow. [http://www.wiomax.com/team/xie/paper/ICAPS12.pdf Schedule-driven coordination for real-time traffic network control]. International Conference on Automated Planning and Scheduling (ICAPS), São Paulo, Brazil, 2012: 323–331.</ref> logistics,<ref name="compare">{{Cite journal | last1 = Máhr | first1 = T. S. | last2 = Srour | first2 = J. | last3 = De Weerdt | first3 = M. | last4 = Zuidwijk | first4 = R. | title = Can agents measure up? A comparative study of an agent-based and on-line optimization approach for a drayage problem with uncertainty | doi = 10.1016/j.trc.2009.04.018 | journal = Transportation Research Part C: Emerging Technologies | volume = 18 | pages = 99–119 | year = 2010 | issue = 1 | bibcode = 2010TRPC...18...99M | citeseerx = 10.1.1.153.770 }}</ref> graphics, manufacturing, [[power system]],<ref name="GEP_1">{{cite book| chapter=Generation Expansion Planning Considering Investment Dynamic of Market Participants Using Multi-agent System| author1=Kazemi, Hamidreza| author2=Liasi, Sahand| author3=Sheikh-El-Eslami, Mohammadkazem| title=2018 Smart Grid Conference (SGC)| chapter-url=https://www.researchgate.net/publication/334765661| date=November 2018| pages=1–6| access-date=8 January 2024| doi=10.1109/SGC.2018.8777904| isbn=978-1-7281-1138-4}}</ref> [[smartgrids]],<ref name=DMA_1>{{cite journal| title=Distributed Multi -Agent System Based Load Frequency Control for Multi- Area Power System in Smart Grid| author1=Singh, Vijay| author2=Samuel, Paulson| url=https://www.researchgate.net/publication/312304154| journal=IEEE Transactions on Industrial Electronics| volume=64| issue=6| pages=5151–5160| date=6 June 2017| access-date=8 January 2024| doi=10.1109/TIE.2017.2668983}}</ref> and the [[Geographic information system|GIS]].

Also, [[Distributed artificial intelligence#Agents and Multi-agent systems|Multi-agent Systems Artificial Intelligence]] (MAAI) are used for simulating societies, the purpose thereof being helpful in the fields of climate, energy, [[epidemiology]], [[conflict management]], child abuse, ....<ref name="newscientist.com">{{Cite web|url=https://www.newscientist.com/article/mg24332500-800-ai-can-predict-your-future-behaviour-with-powerful-new-simulations/|title=AI can predict your future behaviour with powerful new simulations|website=New Scientist}}</ref> 

Some organisations working on using multi-agent system models include Center for Modelling Social Systems,<ref>{{Cite web |title=Center for Modeling Social Systems - Norce |url=https://www.norceresearch.no/en/research-group/cmss |access-date=2025-04-13 |website=NORCE Norwegian Research Centre |language=en}}</ref> Centre for Research in Social Simulation,<ref>{{Cite web |title=Centre for Research in Social Simulation – A multidisciplinary centre bringing together the social sciences and agent-based modelling to promote and support the use of social simulation in research in the human sciences. |url=https://cress.soc.surrey.ac.uk/cresswp/ |access-date=2025-04-13 |language=en-GB}}</ref> Centre for Policy Modelling, Society for Modelling and Simulation International.<ref name="newscientist.com" />

Vehicular traffic with controlled autonomous vehicles can be modelling as a multi-agent system involving crowd dynamics.<ref name="Gong">{{cite journal |last1=Gong |first1=Xiaoqian |last2=Herty |first2=Michael |last3=Piccoli |first3=Benedetto |last4=Visconti |first4=Giuseppe |title=Crowd Dynamics: Modeling and Control of Multiagent Systems |journal=Annual Review of Control, Robotics, and Autonomous Systems |date=3 May 2023 |volume=6 |issue=1 |pages=261–282 |doi=10.1146/annurev-control-060822-123629 |language=en |issn=2573-5144|doi-access=free }}</ref>

Hallerbach et al. discussed the application of agent-based approaches for the development and validation of [[Vehicular automation|automated driving systems]] via a digital twin of the vehicle-under-test and microscopic traffic simulation based on independent agents.<ref>{{cite journal |last1=Hallerbach |first1=S. |last2=Xia |first2=Y. |last3=Eberle |first3=U. |last4=Koester |first4=F. |title=Simulation-Based Identification of Critical Scenarios for Cooperative and Automated Vehicles |journal=SAE International Journal of Connected and Automated Vehicles |volume=1 |issue=2 |page=93 |date=2018 |publisher=SAE International |doi=10.4271/2018-01-1066 |url=https://www.researchgate.net/publication/324194968}}</ref> [[Waymo]] has created a multi-agent simulation environment Carcraft to test algorithms for [[self-driving car]]s.<ref>{{cite news |last1=Madrigal |first1=Story by Alexis C. |title=Inside Waymo's Secret World for Training Self-Driving Cars |url=https://www.theatlantic.com/technology/archive/2017/08/inside-waymos-secret-testing-and-simulation-facilities/537648/ |access-date=14 August 2020 |work=The Atlantic}}</ref><ref>{{cite journal |last1=Connors |first1=J. |last2=Graham |first2=S. |last3=Mailloux |first3=L. |title=Cyber Synthetic Modeling for Vehicle-to-Vehicle Applications |journal=In International Conference on Cyber Warfare and Security |date=2018 |page=594-XI |publisher=Academic Conferences International Limited}}</ref> It simulates traffic interactions between human drivers, pedestrians and automated vehicles. People's behavior is imitated by artificial agents based on data of real human behavior.

== See also ==
{{div col|colwidth=30em|small=yes}}
* [[Comparison of agent-based modeling software]]
* [[Agent-based computational economics]] (ACE)
* [[Artificial brain]]
* [[Artificial intelligence]]
* [[Artificial life]]
* Artificial philosophy
* [[AI mayor]]
* [[Black box]]
* [[Blackboard system]]
* [[Complex systems]]
* [[Discrete event simulation]]
* [[Distributed artificial intelligence]]
* [[Emergence]]
* [[Evolutionary computation]]
* [[Friendly artificial intelligence]]
* [[Game theory]]
* [[Hallucination (artificial intelligence)]]
* [[Human-based genetic algorithm]]
* [[Hybrid intelligent system]]
* [[Knowledge Query and Manipulation Language]] (KQML)
* [[Microbial intelligence]]
* [[Multi-agent planning]]
* [[Multi-agent reinforcement learning]]
* [[Pattern-oriented modeling]]
* [[PlatBox Project]]
* [[Reinforcement learning]]
* [[Scientific community metaphor]]
* [[Self-reconfiguring modular robot]]
* [[Simulated reality]]
* [[Social simulation]]
* [[Software agent]]
* [[Software bot]]
* [[Swarm intelligence]]
* [[Swarm robotics]]
{{div col 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=978-0-471-49691-5}}
* {{cite book |first1=Yoav |last1=Shoham |first2=Kevin |last2=Leyton-Brown |url=http://www.masfoundations.org|title=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 |volume= 2 |issue=2 |pages=1–26 |date=August 2000|url=https://www.researchgate.net/publication/215705246}}
* {{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 |volume=21 |issue=6 |pages=1409–1419 |date=Nov–Dec 1991|url=https://pdfs.semanticscholar.org/7840/bbf6b2fceb014cd3e8eeb2bd81529c7b36b5.pdf |archive-url=https://web.archive.org/web/20170831090048/https://pdfs.semanticscholar.org/7840/bbf6b2fceb014cd3e8eeb2bd81529c7b36b5.pdf |url-status=dead |archive-date=2017-08-31 |doi=10.1109/21.135685 |s2cid=39080989 }}
* ''[[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=978-0-262-23203-6}}
* {{cite book |first=Jacques |last=Ferber |title=Multi-Agent Systems: An Introduction to Artificial Intelligence |publisher=Addison-Wesley |year=1999 |isbn=978-0-201-36048-6}}
* {{cite book |first=Danny |last=Weyns |title=Architecture-Based Design of Multi-Agent Systems|publisher=Springer |year=2010 |isbn=978-3-642-01063-7}}
* {{cite book |last=Sun |first=Ron |author-link=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=978-0-521-83964-8}}
* {{cite book |first1=David |last1=Keil |first2=Dina |last2=Goldin |url=https://archive.org/details/environmentsform0000e4ma/page/68 |title=Indirect Interaction in Environments for Multiagent Systems |journal=Environments for Multiagent Systems II |volume=3830 |pages=[https://archive.org/details/environmentsform0000e4ma/page/68 68–87] |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 |doi=10.1007/11678809_5 |isbn=978-3-540-32614-4 }}
* ''[https://web.archive.org/web/20090114063602/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/ }}
* {{Russell Norvig 2003}}
* {{cite book |first=Maria |last=Fasli |title=Agent-technology for E-commerce |publisher=[[John Wiley & Sons]] |year=2007 |pages=480 |isbn=978-0-470-03030-1}}
* Cao, Longbing, Gorodetsky, Vladimir, Mitkas, Pericles A. (2009). [http://www2.computer.org/portal/web/csdl/doi/10.1109/MIS.2009.45 Agent Mining: The Synergy of Agents and Data Mining], IEEE Intelligent Systems, vol. 24, no. 3, 64-72.

{{Systems}}
{{Informatics}}
{{Authority control}}

{{DEFAULTSORT:Multi-Agent System}}
[[Category:Multi-agent systems| ]]
[[Category:Management theory]]