A Prediction based Similar-taxis Strategy

C. Sun, J. Wang (PRC), and Y. Sun (USA)

Keywords

Evolutionary Computation, Mind Evolutionary Computation, Genetic Algorithms, Similartaxis Strategy

Abstract

In this paper we present a prediction based similartaxis strategy (PBSS) for MEC (Mind Evolutionary Computation), analyze its adaptive ability, and discuss how to choose parameters for the strategy. MEC using PBSS does well in searching flat landscapes. For the test functions in this paper, four algorithms are compared, and they are Simple Genetic Algorithms (SGA), Deterministic Crowding niching GA (DC), Basic MEC (BMEC) and MEC using PBSS. In the experiments, search efficiency of MEC using PBSS is higher by above 90%, compared with those of SGA and DC, and better than basic MEC.

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