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» DFA Learning of Opponent Strategies
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ICMLA
2009
13 years 7 months ago
Multiagent Transfer Learning via Assignment-Based Decomposition
We describe a system that successfully transfers value function knowledge across multiple subdomains of realtime strategy games in the context of multiagent reinforcement learning....
Scott Proper, Prasad Tadepalli
AAAI
2007
14 years 4 days ago
Gender-Sensitive Automated Negotiators
This paper introduces an innovative approach for automated negotiating using the gender of human opponents. Our approach segments the information acquired from previous opponents,...
Ron Katz, Sarit Kraus
NN
2006
Springer
140views Neural Networks» more  NN 2006»
13 years 9 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
NPL
2000
105views more  NPL 2000»
13 years 9 months ago
Online Interactive Neuro-evolution
In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future...
Adrian K. Agogino, Kenneth O. Stanley, Risto Miikk...
IJCAI
2007
13 years 11 months ago
Reinforcement Learning of Local Shape in the Game of Go
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...
David Silver, Richard S. Sutton, Martin Mülle...