Application of Fitness Inference Method with Variable Number of Real Evaluation in Interactive Evolutionary Computation

Abstract

Interactive Evolutionary Computation (IEC) is one of the effective methods for optimization problems which are difficult to formulate the evaluation function such as human sensitivity. This method, however, gives a big burden to the user because he/she himself/herself has to evaluate the candidates of solutions a lot of times. This paper employs a fitness inference method to reduce the burden for evaluation. When fitness inference method is applied to IEC, it can be a problem that the evaluation criterion for user has changed with the passage of time and/or impression given by the effects of other candidates. Because the fitness inference method infers the fitness values of candidates using the information of the actually evaluated solutions and their fitness values in previous generations. This paper proposes the fitness inference method with varying the number of actual evaluation for candidates based on the accuracy of inference for effective update of database. The proposed method can reduce the burden of evaluation following the user's evaluation criterion. This paper applies the proposed method to hearing aid adjustment support system using IEC and investigates the effectiveness of this method.