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» Learning to Play Chess Using Temporal Differences
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ICANN
2010
Springer
14 years 7 months ago
Learning in a Unitary Coherent Hippocampus
Abstract. A previous paper [2] presented a model (UCPF-HC) of the hippocampus as a unitary coherent particle filter, which combines the classical hippocampal roles of associative m...
Charles W. Fox, Tony J. Prescott
61
Voted
CG
2002
Springer
14 years 9 months ago
Learning a Game Strategy Using Pattern-Weights and Self-play
Abstract. This paper demonstrates the use of pattern-weights in order to develop a strategy for an automated player of a non-cooperative version of the game of Diplomacy. Diplomacy...
Ari Shapiro, Gil Fuchs, Robert Levinson
95
Voted
NIPS
2001
14 years 11 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
ICML
2009
IEEE
15 years 10 months ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino
ROMAN
2007
IEEE
191views Robotics» more  ROMAN 2007»
15 years 3 months ago
Learning and Recognition of Object Manipulation Actions Using Linear and Nonlinear Dimensionality Reduction
— In this work, we perform an extensive statistical evaluation for learning and recognition of object manipulation actions. We concentrate on single arm/hand actions but study th...
Isabel Serrano Vicente, Danica Kragic, Jan-Olof Ek...