Efficient reinforcement learning through symbiotic evolution

Machine Learning

Volumn 22, Issue 1-3, 1996, Pages 11-32

  Moriarty, David E ^a   Miikkulainen, Risto ^a  

^a University of Texas at Austin   (United States)

Author keywords

Genetic algorithms; Neural networks; Neuro Evolution; Reinforcement learning

Indexed keywords

EID: 0002318273     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF00114722     Document Type: Article

References (9)

1. Anderson, C. W. (1987). Strategy learning with multilayer connectionist representations Technical Report TR87 509.3, GTE Labs, Waltham, MA.
2. Anderson, C. W. (1989). Learning to control an inverted pendulum using neural networks IEEE Control Systems Magazine. 9:31-37.
3. Barto, A. G., Sutton, R. S., & Anderson. C. W. (1983). Neuronlike adaptive elements that can solve difficult learning control problems. IEEE Transactions on Systems. Man, and Cybernetics, SMC 13:834-846.
4. Belew, R. K., McInerney, J., & Schraudolph, N. N. (1491). Evolving networks: Using the genetic algorithm with connectionist learning. In Farmer, J. D., Langton, C., Rasmussen, S., and Taylor, C., editors. Artificial Life II. Reading, MA. Addison Wesley.
5. Brooks, R. A. (1991). Intelligence without representation Artificial Intelligence, 47:139-159.
6. Collins, R. J., & Jefferson, D. R. (1991). Selection in massively parallel genetic algorithms In Proceedings of the Fourth International Conference on Genetic Algorithms, 249-256. San Matco, CA: Morgan Kaufmann.
7. De Jong, K. A. (1975). An Analysis of the Behavior of a Class of Genetic Adaptive Systems. PhD thesis, The University of Michigan, Ann Arbor, MI.
8. Goldberg, D. E. (1989). Genetic Algorithms in search, Optimization and Machine Learning. Reading, MA: Addison-Wesley.
9. Goldberg, D. E., & Richardson, J. (1987) Genetic algorithms with sharing for multimodal function optimization. In Proceedings of the Second International Conference on Genetic Algorithms, 148-154. San Mateo, CA: Morgan Kaufmann.