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» Evolutionary Algorithms for the Satisfiability Problem
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UPP
2004
Springer
15 years 5 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 6 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
AIPS
2006
15 years 1 months ago
Optimal STRIPS Planning by Maximum Satisfiability and Accumulative Learning
Planning as satisfiability (SAT-Plan) is one of the best approaches to optimal planning, which has been shown effective on problems in many different domains. However, the potenti...
Zhao Xing, Yixin Chen, Weixiong Zhang
CSCLP
2007
Springer
15 years 6 months ago
A Global Filtration for Satisfying Goals in Mutual Exclusion Networks
We formulate a problem of goal satisfaction in mutex networks in this paper. The proposed problem is motivated by problems that arise in concurrent planning. For more efficient sol...
Pavel Surynek