Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Niching methods for genetic algorithms
Niching methods for genetic algorithms
Discovery of subroutines in genetic programming
Advances in genetic programming
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Modeling Building-Block Interdependency
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Collective Intelligence and Braess' Paradox
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Compositional evolution: interdisciplinary investigations in evolvability, modularity, and symbiosis
Compositional evolution: interdisciplinary investigations in evolvability, modularity, and symbiosis
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Scalability problems of simple genetic algorithms
Evolutionary Computation
Learning the ideal evaluation function
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Factorial representations to generate arbitrary search distributions
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Ideal Evaluation from Coevolution
Evolutionary Computation
Compact representations as a search strategy: compression EDAs
Theoretical Computer Science - Foundations of genetic algorithms
A Monotonic Archive for Pareto-Coevolution
Evolutionary Computation
Overcoming hierarchical difficulty by hill-climbing the building block structure
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Hierarchical Co-evolution of Cooperating Agents Acting in the Brain-Arena
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Using over-sampling in a Bayesian classifier EDA to solve deceptive and hierarchical problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Compact genetic codes as a search strategy of evolutionary processes
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
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Genetic algorithms generally use a fixed problem representation that maps variables of the search space to variables of the problem, and operators of variation that are fixed over time. This limits their scalability on non-separable problems. To address this issue, methods have been proposed that coevolve explicitly represented modules. An open question is how modules in such coevolutionary setups should be evaluated. Recently, Pareto-coevolution has provided a theoretical basis for evaluation in coevolution. We define a notion of functional modularity, and objectives for module evaluation based on Pareto-Coevolution. It is shown that optimization of these objectives maximizes functional modularity. The resulting evaluation method is developed into an algorithm for variable length, open ended development of representations called DevRep. DevRep successfully identifies large partial solutions and greatly outperforms fixed length and variable length genetic algorithms on several test problems, including the 1024-bit Hierarchical-XOR problem.