Coevolutionary Life-Time Learning

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 coevolution — 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.

[1]  L. D. Whitley,et al.  Genetic Reinforcement Learning for Neurocontrol Problems , 2004, Machine Learning.

[2]  Geoffrey E. Hinton,et al.  Connectionist Architectures for Artificial Intelligence , 1990, Computer.

[3]  Charles E. Taylor,et al.  Artificial Life II , 1991 .

[4]  W. Daniel Hillis,et al.  Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .

[5]  Hiroaki Kitano,et al.  Empirical Studies on the Speed of Convergence of Neural Network Training Using Genetic Algorithms , 1990, AAAI.

[6]  Jan Paredis,et al.  Co-evolutionary Constraint Satisfaction , 1994, PPSN.

[7]  L. Darrell Whitley,et al.  Optimizing Neural Networks Using FasterMore Accurate Genetic Search , 1989, ICGA.

[8]  Jan Paredis,et al.  Steps towards Coevolutionary Classification Neural Networks , 1994 .

[9]  Jan Paredis,et al.  Coevolutionary Computation , 1995, Artificial Life.

[10]  Scott E. Fahlman,et al.  An empirical study of learning speed in back-propagation networks , 1988 .

[11]  L. Darrell Whitley,et al.  Lamarckian Evolution, The Baldwin Effect and Function Optimization , 1994, PPSN.

[12]  Jan Paredis,et al.  The Symbiotic Evolution of Solutions and Their Representations , 1995, International Conference on Genetic Algorithms.

[13]  Jan Paredis,et al.  The evolution of behavior: some experiments , 1991 .

[14]  David J. Chalmers,et al.  The Evolution of Learning: An Experiment in Genetic Connectionism , 1991 .

[15]  Jan Paredis,et al.  Symbiotic Coevolution for Epistatic Problems , 1996, European Conference on Artificial Intelligence.

[16]  Richard K. Belew,et al.  Evolving networks: using the genetic algorithm with connectionist learning , 1990 .

[17]  Jean-Arcady Meyer,et al.  The Evolution of Behavior: Some Experiments , 1991 .

[18]  W. Hart Adaptive global optimization with local search , 1994 .