33 search results - page 4 / 7 » Reinforcement learning for games: failures and successes |
AGI
2008
13 years 7 months ago
2008
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
AIIDE
2007
13 years 8 months ago
2007
The goal of adaptive game AI is to enhance computercontrolled game-playing agents with (1) the ability to selfcorrect mistakes, and (2) creativity in responding to new situations....
ROBOCUP
2007
Springer
14 years 11 days ago
2007
Springer
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
ICMLA
2009
13 years 4 months ago
2009
We describe a system that successfully transfers value function knowledge across multiple subdomains of realtime strategy games in the context of multiagent reinforcement learning....
AR
2008
13 years 6 months ago
2008
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...