97 search results - page 2 / 20 » Learning against multiple opponents |
ICMAS
1998
13 years 6 months ago
1998
This work presents a lookahead-based exploration strategy for a model-based learning agent that enables exploration of the opponent's behavior during interaction in a multi-a...
ATAL
2011
Springer
12 years 5 months ago
2011
Springer
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
AAMAS
2005
Springer
13 years 5 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...
FLAIRS
2011
12 years 8 months ago
2011
In a competitive game it is important to identify the opponent’s strategy as quickly and accurately as possible so that an effective response can be staged. In this vain, this p...
ATAL
2008
Springer
13 years 7 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...