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NIPS
2008
14 years 11 months ago
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g.,...
Dotan Di Castro, Dmitry Volkinshtein, Ron Meir
ICGA
2008
100views Optimization» more  ICGA 2008»
14 years 10 months ago
Learning the Piece Values for Three Chess Variants
A set of experiments for learning the values of chess pieces is described for the popular chess variants Crazyhouse Chess, Suicide Chess, and Atomic Chess. We follow an establishe...
Sacha Droste, Johannes Fürnkranz
ACL
2010
14 years 8 months ago
Reading between the Lines: Learning to Map High-Level Instructions to Commands
In this paper, we address the task of mapping high-level instructions to sequences of commands in an external environment. Processing these instructions is challenging--they posit...
S. R. K. Branavan, Luke S. Zettlemoyer, Regina Bar...
ECAI
2006
Springer
15 years 1 months ago
Using Emotions for Behaviour-Selection Learning
Emotions play a very important role in human behaviour and social interaction. In this paper we present a control architecture which uses emotions in the behaviour selection proces...
Maria Malfaz, Miguel Angel Salichs
FLAIRS
2008
15 years 9 days ago
Learning Continuous Action Models in a Real-Time Strategy Environment
Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
Matthew Molineaux, David W. Aha, Philip Moore