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GPEM
2011
9 years 4 months ago
Expert-driven genetic algorithms for simulating evaluation functions
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropr...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...
CG
2002
Springer
9 years 9 months ago
A Small Go Board Study of Metric and Dimensional Evaluation Functions
The difficulty to write successful 19x19 go programs lies not only in the combinatorial complexity of go but also in the complexity of designing a good evaluation function containi...
Bruno Bouzy
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
9 years 10 months ago
Genetic algorithms for mentor-assisted evaluation function optimization
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an approp...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...
AAAI
1994
9 years 11 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
SCAI
1997
9 years 11 months ago
On the Well-Behavedness of Important Attribute Evaluation Functions
The class of well-behaved evaluation functions simplifies and makes efficient the handling of numerical attributes; for them it suffices to concentrate on the boundary points in...
Tapio Elomaa, Juho Rousu
AAAI
1998
9 years 11 months ago
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
This paper describes STAGE, a learning approach to automatically improving search performance on optimization problems.STAGElearns an evaluation function which predicts the outcom...
Justin A. Boyan, Andrew W. Moore
FLAIRS
2003
9 years 11 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
AAAI
2006
9 years 11 months ago
Exploring GnuGo's Evaluation Function with a SVM
While computers have defeated the best human players in many classic board games, progress in Go remains elusive. The large branching factor in the game makes traditional adversar...
Christopher Fellows, Yuri Malitsky, Gregory Wojtas...
GECCO
2010
Springer
180views Optimization» more  GECCO 2010»
9 years 11 months ago
Coevolution of heterogeneous multi-robot teams
Evolving multiple robots so that each robot acting independently can contribute to the maximization of a system level objective presents significant scientific challenges. For e...
Matt Knudson, Kagan Tumer
EPS
1995
Springer
10 years 1 months ago
A Survey of Constraint Handling Techniques in Evolutionary Computation Methods
One of the major components of any evolutionary system is the evaluation function. Evaluation functions are used to assign a quality measure for individuals in a population. Where...
Zbigniew Michalewicz
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