Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Genetic programming that ensures programs are original
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolution of the CPG with sensory feedback for bipedal locomotion
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Hi-index | 0.00 |
Genetic Programming (GP) is an evolutionary search algorithm which searches a computer program capable of producing the desired solution for a given problem. For the purpose, it is necessary that GP system has access to a set of features that are at least a superset of the features necessary to solve the problem. However, when the feature set given to GP is redundant, GP suffers substantial loss of its efficiency. This paper presents a new approach in GP to acquire relevant terminals from a redundant set of terminals. We propose the adaptive mutation based on terminal weighting mechanism for eliminating irrelevant terminals from the redundant terminal set. We show empirically that the proposed method is effective for finding relevant terminals and improving performance of GP in the experiments on symbolic regression problems.