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» Learning of Resource Allocation Strategies for Game Playing
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IJCAI
2003
13 years 9 months ago
Learning Minesweeper with Multirelational Learning
Minesweeper is a one-person game which looks deceptively easy to play, but where average human performance is far from optimal. Playing the game requires logical, arithmetic and p...
Lourdes Peña Castillo, Stefan Wrobel
FLAIRS
2003
13 years 9 months ago
Learning Opening Strategy in the Game of Go
In this paper, we present an experimental methodology and results for a machine learning approach to learning opening strategy in the game of Go, a game for which the best compute...
Timothy Huang, Graeme Connell, Bryan McQuade
ICML
2003
IEEE
14 years 8 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
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...
Vincent Conitzer, Tuomas Sandholm
AGENTS
2000
Springer
13 years 11 months ago
A game-theoretic formulation of multi-agent resource allocation
This paper considers resource allocation in a network with mobile agents competing for computational priority. We formulate this problem as a multi-agent game with the players bei...
Jonathan Bredin, Rajiv T. Maheswaran, Çagri...
ISIPTA
2003
IEEE
125views Mathematics» more  ISIPTA 2003»
14 years 1 months ago
Game-Theoretic Learning Using the Imprecise Dirichlet Model
We discuss two approaches for choosing a strategy in a two-player game. We suppose that the game is played a large number of rounds, which allows the players to use observations o...
Erik Quaeghebeur, Gert de Cooman