Evolutionary robot behavior via natural selection based on neural networks
Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527) - Tập 2 - Trang 1509-1514 vol.2
Tóm tắt
The traditional fitness function based methodology of artificial evolution is argued to be inadequate for the construction of entities with behaviors novel to their designers. Evolutionary emergence via natural selection (without an explicit fitness function) is the way forward. This paper primarily considers the question of what to evolve, and focuses on principles of developmental modularity in neural networks. To develop and test the ideas, an artificial world containing autonomous organisms has been created and is described. Experimental results show that the developmental system is well suited to long-term incremental evolution. Novel emergent strategies are identified both from an observer's perspective and in terms of their neural mechanisms.
Từ khóa
#Robots #Neural networks #Artificial neural networks #Artificial intelligence #Organisms #Genetic mutations #Large Hadron Collider #Evolutionary computation #Buildings #Life testingTài liệu tham khảo
channon, 1998, Perpetuating evolutionary emergence, Proc SAB
yaeger, 1993, Computational genetics, physiology, metabolism, neural systems, learning, vision, and behavior or polyworld: Life in a new context, 263
boers, 1992, Biological metaphors and the design of modular artificial neural networks
koza, 1992, Genetic Programming
wang, 2000, Research on combined behavior method for evolutionary robot based on neural network, Journal of Computer research and development, 37, 1457
harvey, 1993, Evolutionary robotics and SAGA: the case for hill crawling and tournament selection
wang, 2000, Research on evolutionary robot behavior using developmental network, Acta Enectronica Sinica, 28, 41
10.1016/0022-5193(68)90079-9
10.1007/3-540-61093-6_3
ray, 1991, An approach to the synthesis of life, Artificial Life II, 371
kitano, 1990, Designing neural networks using genetic algorithms with graph generation system, Complex Systems, 4, 461
zaera, 0, Evolving collective behaviours in synthetic fish, Proc SAB, 635