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» Heuristic Evaluation Functions for General Game Playing
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SAGT
2010
Springer
175views Game Theory» more  SAGT 2010»
13 years 6 months ago
On Learning Algorithms for Nash Equilibria
Can learning algorithms find a Nash equilibrium? This is a natural question for several reasons. Learning algorithms resemble the behavior of players in many naturally arising gam...
Constantinos Daskalakis, Rafael Frongillo, Christo...
GROUP
2009
ACM
14 years 2 months ago
Emergent team coordination: from fire emergency response practice to a non-mimetic simulation game
We take the work practices of fire emergency responders as the basis for developing simulations to teach team coordination. We introduce non-mimetic simulation: economic operation...
Zachary O. Toups, Andruid Kerne, William A. Hamilt...
AAAI
1994
13 years 9 months ago
Evolving Neural Networks to Focus Minimax Search
Neural networks were evolved through genetic algorithms to focus minimax search in the game of Othello. At each level of the search tree, the focus networks decide which moves are...
David E. Moriarty, Risto Miikkulainen
ACMACE
2006
ACM
14 years 1 months ago
Motivated reinforcement learning for non-player characters in persistent computer game worlds
Massively multiplayer online computer games are played in complex, persistent virtual worlds. Over time, the landscape of these worlds evolves and changes as players create and pe...
Kathryn Elizabeth Merrick, Mary Lou Maher
ATAL
2008
Springer
13 years 9 months ago
Searching for approximate equilibria in empirical games
When exploring a game over a large strategy space, it may not be feasible or cost-effective to evaluate the payoff of every relevant strategy profile. For example, determining a p...
Patrick R. Jordan, Yevgeniy Vorobeychik, Michael P...