109 search results - page 2 / 22 » Predicting Opponent Actions by Observation |
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...
CDC
2010
IEEE
12 years 11 months ago
2010
IEEE
This paper studies the evolution of the perceptions of players about the game they are involved in using the framework of hypergame theory. The focus is on developing methods that ...
IJCAI
2007
13 years 6 months ago
2007
Computers have already eclipsed the level of human play in competitive Scrabble, but there remains room for improvement. In particular, there is much to be gained by incorporating...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
ICCBR
2010
Springer
13 years 8 months ago
2010
Springer
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...