93 search results - page 7 / 19 » Agent Learning using Action-Dependent Learning Rates in Comp... |
GECCO
2005
Springer
15 years 5 months ago
2005
Springer
This paper reports on the application of classifier systems to the acquisition of decision-making algorithms for agents in online soccer games. The objective of this research is t...
78
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AAMAS
2006
Springer
14 years 11 months ago
2006
Springer
Abstract. There are many domains in which a multi-agent system needs to maximize a "system utility" function which rates the performance of the entire system, while subje...
109
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ICPR
2006
IEEE
16 years 22 days ago
2006
IEEE
Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition communi...
101
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ATAL
2011
Springer
13 years 11 months ago
2011
Springer
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
143
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AIIDE
2009
15 years 23 days ago
2009
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...