Robustness in the Long Run: Auto-teaching vs Anticipation in Evolutionary Robotics
In Evolutionary Robotics, auto-teaching networks, neural networks that modify their own weights during the life-time of the robot, have been shown to be powerful architectures to develop adaptive controllers. Unfortunately, when run for a longer period of time than that used during evolution, the long-term behavior of such networks can become unpredictable. This paper gives an example of such dangerous behavior, and proposes an alternative solution based on anticipation: as in auto-teaching networks, a secondary network is evolved, but its outputs try to predict the next state of the robot sensors. The weights of the action network are adjusted using some back-propagation procedure based on the errors made by the anticipatory network. First results – in simulated environments – show a tremendous increase in robustness of the long-term behavior of the controller.
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- 1.Meyer, C., Akoulchina, I., Ganascia, J.-G.: Learning Strategies in Games by Anticipation. In: Proc. IJCAI 1997, Morgan Kaufmann, San Francisco (1997)Google Scholar
- 2.Endo, Y., Arkin, R.C.: Anticipatory Robot Navigation by Simultaneously Localizing and Building a Cognitive Map. In: ICOS 2003 – Intl. Conf. on Intelligent Robots and Systems. IEEE/RSJ (2003)Google Scholar
- 3.Harvey, I.: Is there another new factor in evolution? Evolutionary Computation 4(3), 311–327 (1997); Special Issue: 100 Years of the Baldwin EffectGoogle Scholar
- 4.Jordan, M., Rumelhart, D.: Forward models: Supervised learning with a distal teacher. Cognitive Science 16 (1992)Google Scholar
- 7.Nolfi, S., Floreano, D.: How co-evolution can enhance the adaptive power of artificial evolution: implications for evolutionary robotics. In: Husbands, P., Meyer, J.A. (eds.) Proceedings of EvoRobot 1998, pp. 22–38. Springer, Heidelberg (1998)Google Scholar
- 10.Kevin O’Regan, J., Noë, A.: A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences 24(5) (2001)Google Scholar
- 12.Tishby, N., Pereira, F.C., Bialek, W.: The information bottleneck method. In: Proc. 37th Allerton Conf. on Communication, Control and Computing, pp. 368–377 (1999)Google Scholar
- 13.Veloso, M., Stone, P., Bowling, M.: Anticipation as a key for collaboration in a team of agents: A case study in robotic soccer. In: SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, vol. 3839 (1999)Google Scholar