Coevolutionary Life-Time Learning

摘要

This work studies the interaction of evolution and learning. It starts from the coevolutionary genetic algorithm (CGA) introduced earlier. Two techniques - life-time fitness evaluation (LTFE) and predator-prey coevolu-tion - boost the genetic search of a CGA. The partial but continuous nature of LTFE allows for an elegant incorporation of life-time learning (LTL) within CGAs. This way, not only the genetic search but also the LTL component focuses on "not yet solved" problems. The performance of the new algorithm is compared with various other algorithms.