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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 (IA) is anything which perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or may use knowledge. They may be simple or c ...
s.Hu, J.; Bhowmick, P.; Jang, I.; Arvin, F.; Lanzon, A.,
A Decentralized Cluster Formation Containment Framework for Multirobot Systems
IEEE Transactions on Robotics, 2021.
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 Procedural may refer to: * Procedural generation, a term used in computer graphics applications *Procedural knowledge, the knowledge exercised in the performance of some task * Procedural law, a legal concept *Procedural memory, a cognitive scienc ...
approaches,
algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...
ic search or
reinforcement learning Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine ...
.Hu, J.; Bhowmick, P.; Lanzon, A.,
Group Coordinated Control of Networked Mobile Robots with Applications to Object Transportation
IEEE Transactions on Vehicular Technology, 2021.
Despite considerable overlap, a multi-agent system is not always the same as an
agent-based model An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what ...
(ABM). The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which don't 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 Environment most often refers to: __NOTOC__ * Natural environment, all living and non-living things occurring naturally * Biophysical environment, the physical and biological factors along with their chemical interactions that affect an organism or ...
. 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 In developmental psychology and moral, political, and bioethical philosophy, autonomy, from , ''autonomos'', from αὐτο- ''auto-'' "self" and νόμος ''nomos'', "law", hence when combined understood to mean "one who gives oneself one's ...
* 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 * agent mining * scientific communities (e.g., on biological flocking, language evolution, and economics) * dependability and fault-tolerance * robotics, multi-robot systems (MRS), robotic clusters


Frameworks

Frameworks have emerged that implement common standards (such as the FIPA and
OMG OMG may refer to: * Oh my God (sometimes also Oh my Goodness or Oh my Gosh), a common abbreviation, often used in SMS messages and Internet communication Acronyms * OMG is the IATA code for Omega Airport, Omega, Namibia * Operational manoeuvre ...
MASIF standards). These frameworks e.g.
JADE Jade is a mineral used as jewellery or for ornaments. It is typically green, although may be yellow or white. Jade can refer to either of two different silicate minerals: nephrite (a silicate of calcium and magnesium in the amphibole gro ...
, 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 IES technical committee on Industrial Agents.


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 movement of humans, animals, and goods from one location to another. Modes of transport include air, land ( rail and road), water, cable, pipel ...
,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 The European Technology Platform (ETP) for the Electricity Networks of the Future (SmartGrids) is a European Commission initiative that aims at boosting the competitive situation of the European Union in the field of electricity networks, especi ...
and 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, conflict management, child abuse, ....AI can predict your future behaviour with powerful new simulations
/ref> 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. 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 Alphabet Inc, the parent company of Google. Waymo oper ...
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, driver-less car, or robotic car (robo-car), is a car that is capable of traveling without human input.Xie, S.; Hu, J.; Bhowmick, P.; Ding, Z.; Arvin, F.,Distributed Motion Planning for S ...
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 An artificial brain (or artificial mind) is software and hardware with cognitive abilities similar to those of the animal or human brain. Research investigating "artificial brains" and brain emulation plays three important roles in science: #An o ...
*
Artificial intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machine A machine is a physical system using Power (physics), power to apply Force, forces and control Motion, moveme ...
*
Artificial life Artificial life (often abbreviated ALife or A-Life) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemist ...
*
Artificial life framework Artificial Life is a free and open sourced Java framework created to simulate Life. It is a multi-agents framework where each agent runs its own Thread. The agents are split into two different categories: the services and the processes. The servi ...
* Artificial philosophy * AI mayor *
Black box In science, computing, and engineering, a black box is a system which can be viewed in terms of its inputs and outputs (or transfer characteristics), without any knowledge of its internal workings. Its implementation is "opaque" (black). The te ...
* Blackboard system * Complex systems *
Discrete event simulation A discrete-event simulation (DES) models the operation of a system as a ( discrete) sequence of events in time. Each event occurs at a particular instant in time and marks a change of state in the system. Between consecutive events, no change in ...
*
Distributed artificial intelligence Distributed Artificial Intelligence (DAI) also called Decentralized Artificial Intelligence is a subfield of artificial intelligence research dedicated to the development of distributed solutions for problems. DAI is closely related to and a pred ...
*
Emergence In philosophy, systems theory, science, and art, emergence occurs when an entity is observed to have properties its parts do not have on their own, properties or behaviors that emerge only when the parts interact in a wider whole. Emergen ...
*
Evolutionary computation In computer science, evolutionary computation 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 Friendly artificial intelligence (also friendly AI or FAI) refers to hypothetical artificial general intelligence (AGI) that would have a positive (benign) effect on humanity or at least align with human interests or contribute to foster the impro ...
* Game theory * Human-based genetic algorithm * Hybrid intelligent system * Knowledge Query and Manipulation Language (KQML) *
Microbial intelligence Microbial intelligence (known as bacterial intelligence) is the intelligence shown by microorganisms. The concept encompasses complex adaptive behavior shown by single cells, and altruistic or cooperative behavior in populations of like or unlike ...
* Multi-agent planning *
Multi-agent reinforcement learning ] Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. Each agent is motivated by its own rewards, and does acti ...
*
Pattern-oriented modeling Pattern-oriented modeling (POM) is an approach to bottom-up complex systems analysis that was developed to model complex ecological and agent-based systems. A goal of POM is to make ecological modeling more rigorous and comprehensive.Grimm, V.; Ra ...
*
PlatBox Project PlatBox Project, formally known as Boxed Economy Project, is a multi-agent based computer simulation software development project founded by Iba Laboratory at Keio University, Japan. The main work of PlatBox Project is to develop PlatBox Simula ...
*
Reinforcement learning Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine ...
*
Scientific community metaphor In computer science, the scientific community metaphor is a metaphor used to aid understanding scientific communities. The first publications on the scientific community metaphor in 1981 and 1982 involved the development of a programming lan ...
* Self-reconfiguring modular robot * Simulated reality *
Social simulation Social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in computational law, psychology, organizational behavior, sociology, political science, e ...
* 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 Multi-robot systems