David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
This paper presents a GA-based multi-agent reinforce- ment learning bidding approach (GMARLB) for perform- ing multi-agent reinforcement learning. GMARLB inte- grates reinforcement learning, bidding and genetic algo- rithms. The general idea of our multi-agent systems is as follows: There are a number of individual agents in a team, each agent of the team has two modules: Q module and CQ module. Each agent can select actions to be performed at each step, which are done by the Q module. While the CQ module determines at each step whether the agent should continue or relinquish control. Once an agent relinquishes its control, a new agent is selected by bidding algorithms. We applied GA-based GMARLB to the Backgammon game. The experimental results show GMARLB can achieve a su- perior level of performance in game-playing, outperforming PubEval, while the system uses zero built-in knowledge.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Roland Mühlenbernd (2011). Learning with Neighbours. Synthese 183 (S1):87-109.
Ron Sun, Todd Peterson & Edward Merrill, Bottom-Up Skill Learning in Reactive Sequential Decision Tasks.
Pierre Barbaroux & Gilles Enée (2005). Spontaneous Coordination and Evolutionary Learning Processes in an Agent-Based Model. Mind and Society 4 (2):179-195.
Chris Thornton (1997). Brave Mobots Use Representation: Emergence of Representation in Fight-or-Flight Learning. [REVIEW] Minds and Machines 7 (4):475-494.
Added to index2009-06-13
Total downloads15 ( #161,941 of 1,699,816 )
Recent downloads (6 months)9 ( #69,042 of 1,699,816 )
How can I increase my downloads?