Guarding against premature convergence while accelerating evolutionary search

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. Categories and Subject Descriptors I.2.9 [Computing Methodologies]: Artificial Intelligence— Robotics General Terms Experimentation, Algorithms, Reliability Keywords Evolutionary Robotics,...

• Type: Conference
• Year: 2010
• Where: GECCO
• Authors: Josh C. Bongard, Gregory S. Hornby
• Keywords: Continuous Exploration, Evolutionary Algorithms, GECCO 2010, Optimization, Premature Convergence