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GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 8 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
ATAL
2008
Springer
15 years 7 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
HIS
2008
15 years 6 months ago
New Crossover Operator for Evolutionary Rule Discovery in XCS
XCS is a learning classifier system that combines a reinforcement learning scheme with evolutionary algorithms to evolve rule sets on-line by means of the interaction with an envi...
Sergio Morales-Ortigosa, Albert Orriols-Puig, Este...
AIIDE
2009
15 years 6 months ago
Examining Extended Dynamic Scripting in a Tactical Game Framework
Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This...
Jeremy Ludwig, Arthur Farley
DAGSTUHL
2003
15 years 6 months ago
Maximizing Learning Progress: An Internal Reward System for Development
This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. It...
Frédéric Kaplan, Pierre-Yves Oudeyer