David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
Learn more about PhilPapers
This paper addresses automatic partitioning in complex reinforcement learning tasks with multiple agents, without a priori domain knowledge regarding task structures. Partitioning a state/input space into multiple regions helps to exploit the di erential characteristics of regions and di erential characteristics of agents, thus facilitating learning and reducing the complexity of agents especially when function approximators are used. We develop a method for optimizing the partitioning of the space through experience without the use of a priori domain knowledge. The method is experimentally tested and compared to a number of other algorithms. As expected, we found that the multi-agent method with automatic partitioning outperformed single-agent learning.
|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
Karl Tuyls, Ann Nowe, Tom Lenaerts & Bernard Manderick (2004). An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems. Synthese 139 (2):297 - 330.
John Cantwell (2007). A Model for Updates in a Multi-Agent Setting. Journal of Applied Non-Classical Logics 17 (2):183-196.
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.
Ron Sun (2001). Cognitive Science Meets Multi-Agent Systems: A Prolegomenon. Philosophical Psychology 14 (1):5 – 28.
Added to index2010-12-22
Total downloads4 ( #596,354 of 1,938,799 )
Recent downloads (6 months)1 ( #458,338 of 1,938,799 )
How can I increase my downloads?