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ECML
2007
Springer
15 years 8 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
140
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NIPS
2008
15 years 6 months ago
Analyzing human feature learning as nonparametric Bayesian inference
Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
Joseph Austerweil, Thomas L. Griffiths
FLAIRS
2004
15 years 6 months ago
Using Previous Experience for Learning Planning Control Knowledge
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usually, ML techniques are used in isolation from experience that could be obtained...
Susana Fernández, Ricardo Aler, Daniel Borr...
COGSCI
2002
99views more  COGSCI 2002»
15 years 4 months ago
Learning words from sights and sounds: a computational model
This paper presents an implemented computational model of word acquisition which learns directly from raw multimodal sensory input. Set in an information theoretic framework, the ...
Deb Roy, Alex Pentland
CADE
2008
Springer
16 years 4 months ago
MaLARea SG1- Machine Learner for Automated Reasoning with Semantic Guidance
This paper describes a system combining model-based and learning-based methods for automated reasoning in large theories, i.e. on a large number of problems that use many axioms, l...
Geoff Sutcliffe, Jirí Vyskocil, Josef Urban...