60 search results - page 5 / 12 » DFA Learning of Opponent Strategies |
AIIDE
2008
14 years 3 days ago
2008
The quality of AI opponents often leaves a lot to be desired, which poses many attractive challenges for AI researchers. In this respect, Turn-based Strategy (TBS) games are of pa...
COLT
2006
Springer
14 years 1 months ago
2006
Springer
We consider online learning in repeated decision problems, within the framework of a repeated game against an arbitrary opponent. For repeated matrix games, well known results esta...
CIG
2006
IEEE
14 years 3 months ago
2006
IEEE
Abstract— Many games require opponent modelling for optimal performance. The implicit learning and adaptive nature of evolutionary computation techniques offer a natural way to d...
ECAI
2006
Springer
14 years 1 months ago
2006
Springer
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
GECCO
2003
Springer
14 years 3 months ago
2003
Springer
Abstract. Most modern real-time strategy computer games have a sophisticated but fixed ‘AI’ component that controls the computer’s actions. Once the user has learned how suc...