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ECML
2003
Springer
13 years 11 months ago
Could Active Perception Aid Navigation of Partially Observable Grid Worlds?
Due to the unavoidable fact that a robot’s sensors will be limited in some manner, it is entirely possible that it can find itself unable to distinguish between differing state...
Paul A. Crook, Gillian Hayes
ACMACE
2006
ACM
13 years 11 months ago
Motivated reinforcement learning for non-player characters in persistent computer game worlds
Massively multiplayer online computer games are played in complex, persistent virtual worlds. Over time, the landscape of these worlds evolves and changes as players create and pe...
Kathryn Elizabeth Merrick, Mary Lou Maher
AI
1999
Springer
13 years 5 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
ESANN
2008
13 years 7 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
CORR
2010
Springer
187views Education» more  CORR 2010»
13 years 5 months ago
Learning in A Changing World: Non-Bayesian Restless Multi-Armed Bandit
We consider the restless multi-armed bandit (RMAB) problem with unknown dynamics. In this problem, at each time, a player chooses K out of N (N > K) arms to play. The state of ...
Haoyang Liu, Keqin Liu, Qing Zhao