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AIIDE
2006
13 years 10 months ago
The Self Organization of Context for Learning in MultiAgent Games
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Christopher D. White, Dave Brogan
KDD
2010
ACM
286views Data Mining» more  KDD 2010»
13 years 7 months ago
Nonnegative shared subspace learning and its application to social media retrieval
Although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. These factors can ser...
Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Tru...
CG
2008
Springer
13 years 11 months ago
Learning Positional Features for Annotating Chess Games: A Case Study
Abstract. By developing an intelligent computer system that will provide commentary of chess moves in a comprehensible, user-friendly and instructive way, we are trying to use the ...
Matej Guid, Martin Mozina, Jana Krivec, Aleksander...
CSEE
2011
Springer
13 years 20 days ago
Pex4Fun: Teaching and learning computer science via social gaming
Pex4Fun (http://www.pexforfun.com/)from Microsoft Research is a web-based serious gaming environment for teaching computer science. Pex4Fun can be used to teach and learn computer...
Nikolai Tillmann, Jonathan de Halleux, Tao Xie
IAT
2003
IEEE
14 years 2 months ago
Integrating Reinforcement Learning, Bidding and Genetic Algorithms
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bid...
Dehu Qi, Ron Sun