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A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting
intelligent agent In artificial intelligence, an intelligent agent is an entity that Machine perception, perceives its environment, takes actions autonomously to achieve goals, and may improve its performance through machine learning or by acquiring knowledge r ...
s.H. Pan; M. Zahmatkesh; F. Rekabi-Bana; F. Arvin; J. Hu
T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles
IEEE Transactions on Intelligent Transportation Systems, 2025.
Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve.Hu, J.; Turgut, A.; Lennox, B.; Arvin, F.,
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.
Intelligence may include methodic, functional, procedural approaches,
algorithm In mathematics and computer science, an algorithm () is a finite sequence of Rigour#Mathematics, mathematically rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algo ...
ic search or
reinforcement learning Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learnin ...
. With advancements in large language models (LLMs), LLM-based multi-agent systems have emerged as a new area of research, enabling more sophisticated interactions and coordination among agents. 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. Applications where multi-agent systems research may deliver an appropriate approach include online trading, disaster response, target surveillance and social structure modelling.


Concept

Multi-agent systems consist of agents and their environment. Typically multi-agent systems research refers to software agents. 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 or "agent without goals" (such as obstacle, apple or key in any simple simulation) * Active agents with simple goals (like birds in flocking, or wolf–sheep in 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), and dimensionality (whether spatial characteristics are important factors of the environment and the agent considers space in its decision making). 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.


Characteristics

The agents in a multi-agent system have several important characteristics: * Autonomy: agents at least partially independent, self-aware, 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)


Self-organisation and self-direction

Multi-agent systems can manifest self-organisation as well as self-direction and other 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 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 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 A pheromone () is a secreted or excreted chemical factor that triggers a social response in members of the same species. Pheromones are chemicals capable of acting like hormones outside the body of the secreting individual, to affect the behavio ...
", 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 AI problem-solving and control architectures for both single-agent and multiple-agent systems." Research topics include: * agent-oriented software engineering * beliefs, desires, and intentions ( BDI) * cooperation and coordination * distributed constraint optimization (DCOPs) * organization * communication * negotiation * distributed problem solving *
multi-agent learning A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents.H. Pan; M. Zahmatkesh; F. Rekabi-Bana; F. Arvin; J. HuT-STAR: Time-Optimal Swarm Trajectory Planning for Quadroto ...
* agent mining * scientific communities (e.g., on biological flocking, language evolution, and economics) * dependability and fault-tolerance * robotics, multi-robot systems (MRS), robotic clusters * multi-agent systems also present possible applications in microrobotics, 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


Frameworks

Frameworks have emerged that implement common standards (such as the FIPA and OMG MASIF standards). These frameworks e.g. JADE, save time and aid in the standardization of MAS development. 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
IEEE The Institute of Electrical and Electronics Engineers (IEEE) is an American 501(c)(3) organization, 501(c)(3) public charity professional organization for electrical engineering, electronics engineering, and other related disciplines. The IEEE ...
IES technical committee on Industrial Agents. With advancements in large language models (LLMs) such as ChatGPT, LLM-based multi-agent frameworks, such as CAMEL, have emerged as a new paradigm for developing multi-agent applications.


Applications

MAS have not only been applied in academic research, but also in industry. MAS are applied in the real world to graphical applications such as computer games. Agent systems have been used in films. 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 include
transportation Transport (in British English) or transportation (in American English) is the intentional Motion, movement of humans, animals, and cargo, goods from one location to another. Mode of transport, Modes of transport include aviation, air, land tr ...
,Xiao-Feng Xie, S. Smith, G. Barlow
Schedule-driven coordination for real-time traffic network control
International Conference on Automated Planning and Scheduling (ICAPS), São Paulo, Brazil, 2012: 323–331.
logistics, graphics, manufacturing, power system, smartgrids, and the GIS. Also, Multi-agent Systems Artificial Intelligence (MAAI) are used for simulating societies, the purpose thereof being helpful in the fields of climate, energy,
epidemiology Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and Risk factor (epidemiology), determinants of health and disease conditions in a defined population, and application of this knowledge to prevent dise ...
, conflict management, child abuse, .... Some organisations working on using multi-agent system models include Center for Modelling Social Systems, Centre for Research in Social Simulation, Centre for Policy Modelling, Society for Modelling and Simulation International. Vehicular traffic with controlled autonomous vehicles can be modelling as a multi-agent system involving crowd dynamics. Hallerbach et al. discussed the application of agent-based approaches for the development and validation of automated driving systems via a digital twin of the vehicle-under-test and microscopic traffic simulation based on independent agents.
Waymo Waymo LLC, formerly known as the Google Self-Driving Car Project, is an American autonomous driving technology company headquartered in Mountain View, California. It is a subsidiary of Google's parent company (Alphabet Inc., Alphabet Inc). T ...
has created a multi-agent simulation environment Carcraft to test algorithms for
self-driving car A self-driving car, also known as an autonomous car (AC), driverless car, robotic car or robo-car, is a car that is capable of operating with reduced or no human input. They are sometimes called robotaxis, though this term refers specifica ...
s. 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

* Comparison of agent-based modeling software * Agent-based computational economics (ACE) * Artificial brain *
Artificial intelligence Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of re ...
* Artificial life * Artificial philosophy * AI mayor * Black box * Blackboard system *
Complex systems A complex system is a system composed of many components that may interact with one another. Examples of complex systems are Earth's global climate, organisms, the human brain, infrastructure such as power grid, transportation or communication s ...
* Discrete event simulation * Distributed artificial intelligence *
Emergence In philosophy, systems theory, science, and art, emergence occurs when a complex entity has properties or behaviors that its parts do not have on their own, and emerge only when they interact in a wider whole. Emergence plays a central rol ...
*
Evolutionary computation Evolutionary computation from computer science is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms. In technical terms ...
* Friendly artificial intelligence *
Game theory Game theory is the study of mathematical models of strategic interactions. It has applications in many fields of social science, and is used extensively in economics, logic, systems science and computer science. Initially, game theory addressed ...
* 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 Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learnin ...
* Scientific community metaphor * Self-reconfiguring modular robot * Simulated reality * Social simulation * Software agent * Software bot * Swarm intelligence * Swarm robotics


References


Further reading

* * * * * '' The Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS)'' * * * * * *
Whitestein Series in Software Agent Technologies and Autonomic Computing
', published by Springer Science+Business Media Group * * * * Cao, Longbing, Gorodetsky, Vladimir, Mitkas, Pericles A. (2009)
Agent Mining: The Synergy of Agents and Data Mining
IEEE Intelligent Systems, vol. 24, no. 3, 64-72. {{DEFAULTSORT:Multi-Agent System Management theory