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» High-level reinforcement learning in strategy games
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NN
2006
Springer
140views Neural Networks» more  NN 2006»
13 years 8 months ago
Neural mechanism for stochastic behaviour during a competitive game
Previous studies have shown that non-human primates can generate highly stochastic choice behaviour, especially when this is required during a competitive interaction with another...
Alireza Soltani, Daeyeol Lee, Xiao-Jing Wang
AAAI
2010
13 years 10 months ago
Multi-Agent Learning with Policy Prediction
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Chongjie Zhang, Victor R. Lesser
CEC
2010
IEEE
13 years 9 months ago
Coevolutionary Temporal Difference Learning for small-board Go
—In this paper we apply Coevolutionary Temporal Difference Learning (CTDL), a hybrid of coevolutionary search and reinforcement learning proposed in our former study, to evolve s...
Krzysztof Krawiec, Marcin Szubert
AIIDE
2008
13 years 11 months ago
Intelligent Trading Agents for Massively Multi-player Game Economies
As massively multi-player gaming environments become more detailed, developing agents to populate these virtual worlds as capable non-player characters poses an increasingly compl...
John Reeder, Gita Sukthankar, Michael Georgiopoulo...
SIGIR
2003
ACM
14 years 1 months ago
Distributed Web Search as a Stochastic Game
Distributed search systems are an emerging phenomenon in Web search, in which independent topic-specific search engines provide search services, and metasearchers distribute user...
Rinat Khoussainov, Nicholas Kushmerick