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Multi-agent
A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents.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 Scientific method, methodic, Function (computer science), functional, Algorithm, procedural approaches, algorithmic search algorithm, search or reinforcement learning.Hu, J.; Bhowmick, P.; Lanzon, A.,Group Coordinated Control of Networked Mobile Robots with Applications to Object Transportation IEEE Transacti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multi-agent 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 actions to advance its own interests; in some environments these interests are opposed to the interests of other agents, resulting in complex group dynamics. Multi-agent reinforcement learning is closely related to game theory and especially repeated games, as well as multi-agent systems. Its study combines the pursuit of finding ideal algorithms that maximize rewards with a more sociological set of concepts. While research in single-agent reinforcement learning is concerned with finding the algorithm that gets the biggest number of points for one agent, research in multi-agent reinforcement learning evaluates and quantifies social metrics, such as cooperation, reciprocity, equity, social influence, language and discrimination. Definition ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Java Agent Development Framework
Java Agent Development Framework, or JADE, is a software framework for the development of intelligent agents, implemented in Java. JADE system supports coordination between several agents FIPA and provides a standard implementation of the communication language FIPA-ACL, which facilitates the communication between agents and allows the services detection of the system. JADE was originally developed by Telecom Italia and is distributed as free software. Resume JADE is a middleware which facilitates the development of multi-agent systems under the standard FIPA for which purpose it creates multiple containers for agents, each of them can run on one or more systems. It's understood that a set of containers constitutes a platform. JADE provides: * An environment where JADE agents are executed * Class libraries to create agents using heritage and redefinition of behaviors * A graphical toolkit to monitoring and managing the platform of intelligent agents History JADE was i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
KQML
The Knowledge Query and Manipulation Language, or KQML, is a language and protocol for communication among software agents and knowledge-based systems. It was developed in the early 1990s as part of the DARPA knowledge Sharing Effort, which was aimed at developing techniques for building large-scale knowledge bases which are shareable and reusable. While originally conceived of as an interface to knowledge based systems, it was soon repurposed as an Agent communication language.Tim Finin; Jay Weber; Gio Wiederhold; Michael Gensereth; Richard Fritzson; Donald McKay; James McGuire; Richard Pelavin; Stuart Shapiro; Chris BeckDRAFT Specification of the KQML Agent-Communication Language (PostScript) June 15, 1993. Work on KQML was led by Tim Finin of the University of Maryland, Baltimore County and Jay Weber of EITech and involved contributions from many researchers. The KQML message format and protocol can be used to interact with an intelligent system, either by an application progra ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge). The environment is typically stated in the form of a Markov decision process (MDP), because many reinforcement learning algorithms for this context use dynamic programming techniques. The main difference between the classical dynamic programming methods and reinforcement learning algorithms is that the latter do not assume knowledge of an exact mathematica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Agent Mining
Agent mining is an interdisciplinary area that synergizes multiagent systems with data mining and machine learning. The interaction and integration between multiagent systems and data mining have a long history. The very early work on agent mining focused on agent-based knowledge discovery, agent-based distributed data mining, and agent-based distributed machine learning, and using data mining to enhance agent intelligence. The International Workshop on Agents and Data Mining Interaction has been held for more than 10 times, co-located with the International Conference on Autonomous Agents and Multi-Agent Systems. Several proceedings are available from Springer Lecture Notes in Computer Science ''Lecture Notes in Computer Science'' is a series of computer science books published by Springer Science+Business Media since 1973. Overview The series contains proceedings, post-proceedings, monographs, and Festschrifts. In addition, tutorial .... References {{reflist Data m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Foundation For Intelligent Physical Agents
The Foundation for Intelligent Physical Agents (FIPA) is a body for developing and setting computer software standards for heterogeneous and interacting agents and agent-based systems. FIPA was founded as a Swiss not-for-profit organization in 1996 with the ambitious goal of defining a full set of standards for both implementing systems within which agents could execute (agent platforms) and specifying how agents themselves should communicate and interoperate in a standard way. Within its lifetime the organization's membership included several academic institutions and a large number of companies including Hewlett Packard, IBM, BT (formerly British Telecom), Sun Microsystems, Fujitsu and many more. A number of standards were proposed, however, despite several agent platforms adopting the "FIPA standard" for agent communication it never succeeded in gaining the commercial support which was originally envisaged. The Swiss organization was dissolved in 2005 and an IEEE stan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 complex — a thermostat is considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm, a state, or a biome. Leading AI textbooks define "artificial intelligence" as the "study and design of intelligent agents", a definition that considers goal-directed behavior to be the essence of intelligence. Goal-directed agents are also described using a term borrowed from economics, "rational agent". An agent has an "objective function" that encapsulates all the IA's goals. Such an agent is designed to create and execute whatever plan will, upon completion, maximize the expected value of the objective function. For example, a reinforcement learning agent has a "reward function ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Agent Communication Language
Agent Communication Language (ACL), proposed by the Foundation for Intelligent Physical Agents (FIPA), is a proposed standard language for agent communications. Knowledge Query and Manipulation Language (KQML) is another proposed standard. The most popular ACLs are: * FIPA-ACL (by the Foundation for Intelligent Physical Agents, a standardization consortium) * KQML (Knowledge Query and Manipulation Language) Both rely on speech act theory developed by Searle in the 1960s and enhanced by Winograd and Flores in the 1970s. They define a set of performatives, also called Communicative Acts, and their meaning (e.g. ask-one). The content of the performative is not standardized, but varies from system to system. To make agents understand each other they have to not only speak the same language, but also have a common ontology. An ontology is a part of the agent's knowledge base that describes what kind of things an agent can deal with and how they are related to each other. Examples ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cooperative Distributed Problem Solving
In computing cooperative distributed problem solving is a network of semi-autonomous processing nodes working together to solve a problem, typically in a multi-agent system. That is concerned with the investigation of problem subdivision, sub-problem distribution, results synthesis, optimisation of problem solver coherence and co-ordination. It is closely related to distributed constraint programming and distributed constraint optimization; see the links below. Aspects of CDPS * Neither global control or global data storage – no individual CDPS problem solver (agent) has sufficient information to solve the entire problem. * Control and data are distributed * Communication is slower than computation, therefore: ** Loose coupling between problem solvers ** Efficient protocols (not too much communication overhead) ** problems should be modular, coarse grained * Any unique node is a potential bottleneck ** Organised behaviour is hard to guarantee since no one node has the complete pi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Consensus Dynamics
Consensus dynamics or agreement dynamics is an area of research lying at the intersection of systems theory and graph theory. A major topic of investigation is the agreement or consensus problem in multi-agent systems that concerns processes by which a collection of interacting agents achieve a common goal. Networks of agents that exchange information to reach consensus include: physiological systems, gene networks, large-scale energy systems and fleets of vehicles on land, in the air or in space. The agreement protocol or consensus protocol is an unforced dynamical system that is governed by the interconnection topology and the initial condition for each agent. Other problems are the rendezvous problem, synchronization, flocking, formation control. One solution paradigm is distributed constraint reasoning. To investigate the argumentation of different subjects, a simulation is a useful tool. It can be measured, if an argument provides an additional truth value for a debate. See als ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
