Introduction to probability and statistics (7th ed.)
Introduction to probability and statistics (7th ed.)
Introduction to algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Phase transitions and the search problem
Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Hyperplane Ranking in Simple Genetic Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Epistasis in Genetic Algorithms: An Experimental Design Perspective
Proceedings of the 6th International Conference on Genetic Algorithms
Genetic algorithms as function optimizers
Genetic algorithms as function optimizers
Predicting epistasis from mathematical models
Evolutionary Computation
Efficient Linkage Discovery by Limited Probing
Evolutionary Computation
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Extended probe method for linkage discovery over high-cardinality alphabets
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Matrix interpretation of generalized embedded landscape
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Detecting the epistatic structure of generalized embedded landscape
Genetic Programming and Evolvable Machines
Efficient linkage discovery by limited probing
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Approximating the distribution of fitness over hamming regions
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
Generalized embedded landscape and its decomposed representation
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Constant time steepest descent local search with lookahead for NK-landscapes and MAX-kSAT
Proceedings of the 14th annual conference on Genetic and evolutionary computation
An empirical evaluation of o(1) steepest descent for NK-Landscapes
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Fitness function distributions over generalized search neighborhoods in the q-ary hypercube
Evolutionary Computation
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In this paper we introduce embedded landscapes as an extension of NK landscapes and MAXSAT problems. This extension is valid for problems where the representation can be expressed as a simple sum of subfunctions over subsets of the representation domain. This encompasses many additive constraint problems and problems expressed as the interaction of subcomponents, where the critical features of the subcomponents are represented by subsets of bits in the domain. We show that embedded landscapes of fixed maximum epistasis K are exponentially sparse in epistatic space with respect to all possible functions. We show we can compute many important statistical features of these functions in polynomial time including all the epistatic interactions and the statistical moments of hyperplanes about the function mean and hyperplane mean. We also show that embedded landscapes of even small fixed K can be NP-complete. We can conclude that knowing the epistasis and many of the hyperplane statistics is not enough to solve the exponentially difficult part of these general problems and that the difficulty of the problem lies not in the epistasis itself but in the interaction of the epistatic parts.