576 search results - page 1 / 116 » Improving Offensive Performance Through Opponent Modeling |
AIIDE
2009
13 years 6 months ago
2009
Although in theory opponent modeling can be useful in any adversarial domain, in practice it is both difficult to do accurately and to use effectively to improve game play. In thi...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
Opponent models are necessary in games where the game state is only partially known to the player, since the player must infer the state of the game based on the opponent’s acti...
ATAL
2008
Springer
13 years 6 months ago
2008
Springer
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
IDEAL
2009
Springer
13 years 9 months ago
2009
Springer
Opponent modeling is a skill in multi-agent systems (MAS) which attempts to create a model of the behavior of the opponent. This model can be used to predict the future actions of ...
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...