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S-DLCAM: A Self-Design and Learning Cooperative Agent Model for Adaptive Multi-agent Systems
2013
2013 Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises
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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. ...
Keywords-Adaptive Multi-Agent Systems; Cooperative Agent; Self-Design and Learning Cooperative Agent Model.
I. ...
S-DLCAM: A Self-Design and Learning Cooperative Agent Model for Adaptive Multi-Agent Systems Wafa M EF T EH * , * * , Frédéric M IGEON * , Marie-Pierre GLEIZES * , and Faiez GARGOU RI * * *University of ...
doi:10.1109/wetice.2013.58
dblp:conf/wetice/MeftehMGG13a
fatcat:pholshjqj5grrn3x2stlpabc74
Adaptive fuzzy iterative learning control with initial-state learning for coordination control of leader-following multi-agent systems
2014
Fuzzy sets and systems (Print)
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We propose a distributed adaptive fuzzy iterative learning control (ILC) algorithm to deal with coordination control problems in leader-following multi-agent systems in which each follower agent has unknown ...
A fuzzy learning component is an important learning tool in the protocol, and combined time-domain and iteration-domain adaptive laws are used to tune the controller parameters. ...
Moreover, to combine the characteristics of ILC and multi-agent systems, we use distributed initial-state learning. ...
doi:10.1016/j.fss.2013.10.010
fatcat:dne4g7rulbbzbelfnkitq4roxu
Cooperative Adaptive Learning Control for a Group of Nonholonomic UGVs by Output Feedback
[chapter]
2020
Multi Agent Systems - Strategies and Applications
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In addition, any vehicle in the system is able to learn the knowledge of unmodeled dynamics along the union of trajectories experienced by all vehicle agents, such that the learned knowledge can be re-used ...
The learning-based tracking convergence and consensus learning results, as well as using learned knowledge for tracking experienced trajectories, are shown using the Lyapunov method. ...
An observer and RBFNN-based adaptive learning control algorithm is developed for a multi-vehicle system, such that each vehicle agent will be able to follow the desired reference trajectory. iii. ...
doi:10.5772/intechopen.87038
fatcat:a6k5rnebavazvfvyuoai2humwu
Design of an Adaptive e-Learning System based on Multi-Agent Approach and Reinforcement Learning
2021
Engineering, Technology & Applied Science Research
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In this paper, a design of an adaptative e-learning system based on a multi-agent approach and reinforcement learning is presented. ...
The application of the multi-agent approach in adaptive e-learning systems can enhance the learning process quality by customizing the contents to students' needs. ...
.: Design of an Adaptive e-Learning System based on Multi-Agent Approach and …
Fig. 4 . 4 Role and task model of agents. ...
doi:10.48084/etasr.3905
fatcat:n4vy5awym5cy3hrkj5tk3u4yhu
Improving the adaptability of multi-agent based E-learning systems
2018
Advances in Distributed Computing and Artificial Intelligence Journal
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This paper presents a multi-agent-based e-learning system, as an extension to (Al-Tarabily, 2018). ...
KEYWORD ABSTRACT multi-agent systems; e-learning; clustering E-Learning is a new learning approach that involves the use of electronic technologies to access education outside of a conventional classroom ...
The results of the test demonstrate that the proposed extension to the system developed by (Al-Tarabily, 2018) is valid. ...
doi:10.14201/adcaij20187516
fatcat:sxqsoado2zcjxpk33bpf6fjdte
Online adaptive learning for team strategies in multi-agent systems
2010
The Journal of Defence Modeling and Simulation: Applications, Methodology, Technology
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His current research interests include: multi-agent systems, pattern recognition, and machine learning. He is also the University Relations Liaison, National Auto motive Center (NAC) at the U.S. ...
This learning approach is based on RL techniques. 7,8 A survey on multi-agent RL is presented by Busoniu et al. 6 It is a general method for solving optimal decision problems for general non-linear dynamical ...
1 --3 3 2 3 1 3 T 1 1 11 T 21 11 1 T 1 T 3 2 T 2 1 3 (51) and the second actor (second player) NN be tuned as ...
doi:10.1177/1548512910382002
fatcat:xa4ljml3hzgdvfmoxnbf4owg3m
Adaptive Design of Role Differentiation by Division of Reward Function in Multi-Agent Reinforcement Learning
2010
SICE Journal of Control Measurement and System Integration
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., partial observation, credit assignment, and concurrent learning in multi-agent reinforcement learning. ...
In many conventional approaches, each agent estimates hidden states, e.g., sensor inputs, positions, and policies of other agents, and reduces the uncertainty in the partially-observable Markov decision ...
Because of the socially dynamic property of a multi-agent system, it is difficult for participating agents to achieve multi-agent reinforcement learning tasks. ...
doi:10.9746/jcmsi.3.26
fatcat:lvqmi5cs2jh5xotwekltcv6rbe
Cooperative and Adaptive Optimal Output Regulation of Discrete-Time Multi-Agent Systems Using Reinforcement Learning
2018
2018 IEEE International Conference on Real-time Computing and Robotics (RCAR)
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This paper proposes an original data-driven intelligent control solution to the cooperative output regulation problem of discrete-time multi-agent systems. ...
Based on the combination of internal model principle and reinforcement learning, a distributed suboptimal controller is learned realtime via online input-state data collected from system trajectories. ...
output regulation problems for discrete-time multi-agent systems. ...
doi:10.1109/rcar.2018.8621852
dblp:conf/rcar/GaoLOJYL18
fatcat:54juphy4obeinlolykvrbrfw3y
Agent memory and adaptation in multi-agent systems
2003
Proceedings of the second international joint conference on Autonomous agents and multiagent systems - AAMAS '03
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The agents use memory to estimate the global state of the system from individual observations and adjust their actions accordingly. ...
We describe a general mechanism for adaptation in multiagent systems in which agents modify their behavior based on their memory of past events. ...
The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any ...
doi:10.1145/860700.860703
fatcat:zn7ntamqsjcc7dad27n6qoah4u
Agent memory and adaptation in multi-agent systems
2003
Proceedings of the second international joint conference on Autonomous agents and multiagent systems - AAMAS '03
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The agents use memory to estimate the global state of the system from individual observations and adjust their actions accordingly. ...
We describe a general mechanism for adaptation in multiagent systems in which agents modify their behavior based on their memory of past events. ...
The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any ...
doi:10.1145/860575.860703
dblp:conf/atal/LermanG03
fatcat:ykcwkgih35c2jjcsm3kmcyk3jq
Reasoning About Adaptivity of Agents and Multi-agent Systems
2012
2012 IEEE 17th International Conference on Engineering of Complex Computer Systems
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Although adaptivity is a central feature of agents and multi-agent systems (MAS), there is no precise definition of it in the literature. What does it mean for an agent or for a MAS to be adaptive? ...
How can we reason about and measure the ability of agents and MAS to adapt? In this paper, we provide a formal definition of adaptivity of agents and MAS aimed at addressing these issues. ...
Multi-agent systems (MAS) exhibit both forms of adaptivity. ...
doi:10.1109/iceccs20050.2012.6299229
fatcat:ycskegw3unewhbzeis4j7fjlxu
An adaptative agent architecture for holonic multi-agent systems
2008
ACM Transactions on Autonomous and Adaptive Systems
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Adaptative Agent Architecture for Holonic Multi-Agent Systems · 5
Fig. 1. ...
An Adaptative Agent Architecture for Holonic
Multi-Agent Systems
VINCENT HILAIRE
ABDER KOUKAM
and
SEBASTIAN RODRIGUEZ
Systems and Transportation laboratory
UTBM
90010 Belfort Cedex, FRANCE
Self-organized ...
doi:10.1145/1342171.1342173
fatcat:k3oetngfubfg7oeudegzltx6oi
Intelligent Collaboration Environment in Multi-Agent System Enabling Software Dynamic Integration and Adaptive Evolving
[chapter]
2011
Multi-Agent Systems - Modeling, Control, Programming, Simulations and Applications
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Through wrapping legacy systems www.intechopen.com Multi-Agent Systems -Modeling, Control, Programming, Simulations and Applications 244 and newly-developed systems into agents which has the characteristics ...
In this chapter, the agents are applied to system integration to achieve dynamic system integration and adaptive evolving, through packing the sub-systems into the agents and the communication and collaboration ...
System Enabling Software Dynamic Integration and Adaptive Evolving
Multi-Agent Systems -Modeling, Control, Programming, Simulations and Applications ...
doi:10.5772/15161
fatcat:4bmyh6syvjcdzilf3jgykx54fm
A Multi-Agent Self-Adaptive Multi-Objective Genetic Algorithm
2015
International Journal of Intelligent Engineering and Systems
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Agent also possesses some knowledge of the environment and can learn itself while evolving, in order to adapt itself to the environment better and enhance its viability. ...
A new multi-objective genetic algorithm based on Multi-Agent Self-Adaptive Genetic Algorithm(MASAGA) is proposed, in which the evolution parameters are adjusted adaptively in the evolutionary process and ...
Agent also possesses some knowledge of the environment and can learn itself while evolving, in order to adapt itself to the environment better and enhance its viability. ...
doi:10.22266/ijies2015.0630.02
fatcat:un7ewmoqdbgpfgwib6mzqemjde
Optimal adaptive leader-follower consensus of linear multi-agent systems: Known and unknown dynamics
2015
Journal of Artificial Intelligence and Data Mining
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The decoupling of the multi-agent system global error dynamics facilitates the employment of policy iteration and optimal adaptive control techniques to solve the leaderfollower consensus problem under ...
In this paper, the optimal adaptive leader-follower consensus of linear continuous time multi-agent systems is considered. The error dynamics of each player depends on its neighbors' information. ...
systems, we wish to achieve synchronization in the multi-agent system simultaneously optimizing some performance specifications on the agents. ...
doi:10.5829/idosi.jaidm.2015.03.01.11
fatcat:acjqisj2ujbrjkzzwei4coqr4u
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