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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 12 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
COLT
1994
Springer
15 years 11 months ago
An Optimal Parallel Algorithm for Learning DFA
: Sequential algorithms given by Angluin 1987 and Schapire 1992 learn deterministic nite automata DFA exactly from Membership and Equivalence queries. These algorithms are feasible...
José L. Balcázar, Josep Díaz,...
ATAL
2006
Springer
15 years 11 months ago
Ontology-guided learning to improve communication between groups of agents
We present a general method for agents using ontologies as part of their knowledge representation to teach each other concepts to improve their communication and thus cooperation ...
Mohsen Afsharchi, Behrouz H. Far, Jörg Denzin...
ATAL
2006
Springer
15 years 11 months ago
The use of agents in human learning systems
This paper examines agent-based systems designed for a variety of human learning tasks. These are typically split into two areas: "training", which generally refers to a...
Elizabeth Sklar, Debbie Richards
189
Voted
ECML
2006
Springer
15 years 11 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....