93 search results - page 7 / 19 » Agent Learning using Action-Dependent Learning Rates in Comp... |
GECCO
2005
Springer
14 years 1 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...
AAMAS
2006
Springer
13 years 7 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...
ICPR
2006
IEEE
14 years 8 months 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...
ATAL
2011
Springer
12 years 7 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...
AIIDE
2009
13 years 8 months 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...