NDLI: Multi-agent coordination method based on fuzzy Q-learning

Content Provider	IEEE Xplore Digital Library
Author	Jun Peng Miao Liu Min Wu Xiaoyong Zhang Kuo-Chi Lin
Copyright Year	2008
Description	Author affiliation: Sch. of Inf. Sci. & Eng., Central South Univ., Changsha (Jun Peng; Miao Liu; Min Wu; Xiaoyong Zhang)
Abstract	Traditional reinforcement learning algorithm can only solve the learning problem of the intelligent agent with discrete state space and discrete action space. This paper studies the coordination of multiple intelligent agents in a complicated dynamic environment with uncertainty. A coordination model based on the fuzzy Q-learning technique is suggested. This model uses fuzzy logic to generalize the agentpsilas continuous state space. Every agent, when making decisions on its actions, needs to consider the influences of other agents to the environment. The agent first evaluates the actions they select, then, uses the fuzzy Q-learning to learn their action strategy. In the process, the action keeps improving and the conflicts among agents can be resolved. This model was used in the RoboCup soccer simulation game and the simulation results showed that the performance of attacking is obviously improved.
Starting Page	5411
Ending Page	5416
File Size	266870
Page Count	6
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4593811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent agent Educational institutions Electronic mail Information science Automation Computational modeling Materials RoboCup multi-agent system fuzzy Q-learning multi-agent coordination
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A multi-agent task allocation strategy based on artificial immune system

Fault diagnosis model for coking system based on multi-agent

Emergent behavior research based on multi-agent coevolution mechanism

Constructing Adaptive Individual Learning Environment Based on Multi-agent System

Learning of keepaway task for RoboCup soccer agent based on Fuzzy Q-Learning

A coordination model using fuzzy reinforcement learning for multi-agent system

Research on Agent Coordination Controller Based On Fuzzy Petri Nets

Research on Intelligent CAPP System Based on Multi-agent System

The research on GM(1,1) based on simple Gaussian function transformation

Multi-agent coordination method based on fuzzy Q-learning

Similar Documents

A multi-agent task allocation strategy based on artificial immune system

Fault diagnosis model for coking system based on multi-agent

Emergent behavior research based on multi-agent coevolution mechanism

Constructing Adaptive Individual Learning Environment Based on Multi-agent System

Learning of keepaway task for RoboCup soccer agent based on Fuzzy Q-Learning

A coordination model using fuzzy reinforcement learning for multi-agent system

Research on Agent Coordination Controller Based On Fuzzy Petri Nets

Research on Intelligent CAPP System Based on Multi-agent System

The research on GM(1,1) based on simple Gaussian function transformation

Multi-agent coordination method based on fuzzy Q-learning