Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Problem difficulty for tabu search in job-shop scheduling
Artificial Intelligence
Proceedings of the 5th International Conference on Genetic Algorithms
Building Better Test Functions
Proceedings of the 6th International Conference on Genetic Algorithms
Modeling Building-Block Interdependency
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Critical Examination of the Schema Theorem
A Critical Examination of the Schema Theorem
Combining competent crossover and mutation operators: a probabilistic model building approach
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Conquering hierarchical difficulty by explicit chunking: substructural chromosome compression
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Representation development from pareto-coevolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Compact genetic codes as a search strategy of evolutionary processes
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Crossover: the divine afflatus in search
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Towards memoryless model building
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Large-Scale Optimization of Non-separable Building-Block Problems
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Dependency structure matrix, genetic algorithms, and effective recombination
Evolutionary Computation
The creativity potential within evolutionary algorithms
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Can selfish symbioses effect higher-level selection?
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part II
Symbiosis enables the evolution of rare complexes in structured environments
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part II
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
HYPERION: a recursive hyper-heuristic framework
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Effects of discrete hill climbing on model building forestimation of distribution algorithms
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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The Building Block Hypothesis suggests that Genetic Algorithms (GAs) are well-suited for hierarchical problems, where efficient solving requires proper problem decomposition and assembly of solution from sub-solution with strong non-linear interdependencies. The paper proposes a hill-climber operating over the building block (BB) space that can efficiently address hierarchical problems. The new Building Block Hill-Climber (BBHC) uses hill-climb search experience to learn the problem structure. The neighborhood structure is adapted whenever new knowledge about the underlaying BB structure is incorporated into the search. This allows the method to climb the hierarchical structure by revealing and solving consecutively the hierarchical levels. It is expected that for fully non-deceptive hierarchical BB structures the BBHC can solve hierarchical problems in linearithmic time. Empirical results confirm that the proposed method scales almost linearly with the problem size thus clearly outperforms population based recombinative methods.