62 search results - page 1 / 13 » Learning and Exploiting Relative Weaknesses of Opponent Agen... |
AAMAS
2005
Springer
13 years 4 months ago
2005
Springer
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
ATAL
2010
Springer
13 years 5 months ago
2010
Springer
Video games provide a rich testbed for artificial intelligence methods. In particular, creating automated opponents that perform well in strategy games is a difficult task. For in...
AAAI
2008
13 years 6 months ago
2008
We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
ATAL
2008
Springer
13 years 6 months ago
2008
Springer
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE