Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Robot shaping: developing autonomous agents through learning
Artificial Intelligence
ALPS: the age-layered population structure for reducing the problem of premature convergence
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Parameter space structure of continuous-time recurrent neural networks
Neural Computation
How novelty search escapes the deceptive trap of learning to learn
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Steady-state ALPS for real-valued problems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolving 3d morphology and behavior by competition
Artificial Life
Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolution of central pattern generators for bipedal walking in areal-time physics environment
IEEE Transactions on Evolutionary Computation
Innocent Until Proven Guilty: Reducing Robot Shaping From Polynomial to Linear Time
IEEE Transactions on Evolutionary Computation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
How to promote generalisation in evolutionary robotics: the ProGAb approach
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Bayesian networks learning for strategies in artificial life
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Encouraging behavioral diversity in evolutionary robotics: An empirical study
Evolutionary Computation
Efficient training set use for blood pressure prediction in a large scale learning classifier system
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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The fundamental dichotomy in evolutionary algorithms is that between exploration and exploitation. Recently, several algorithms [8, 9, 14, 16, 17, 20] have been introduced that guard against premature convergence by allowing both exploration and exploitation to occur simultaneously. However, continuous exploration greatly increases search time. To reduce the cost of continuous exploration we combine one of these methods (the age-layered population structure (ALPS) algorithm [8, 9]) with an early stopping (ES) method [2] that greatly accelerates the time needed to evaluate a candidate solution during search. We show that this combined method outperforms an equivalent algorithm with neither ALPS nor ES, as well as regimes in which only one of these methods is used, on an evolutionary robotics task.