Abstract
In the paper a synthesis of developmental and evolutionary modeling is proposed. The synthesis is demonstrated by adaptive autonomous agents capable of developing, learning, and evolving in an artificial environment. The main merits of the proposed synthesis is a simplification of the genetic information and environmental embodiment. The created behaviors of light following and obstacle avoidance are simple, but verify the approach with a capability to scale up the model.
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Akira Onitsuka, Jari Vaario, Katsunori Shimohara, and Kanji Ueda. Behavior generation based on enhanced dIa model at neural network. In J-H. Kim and X. Yao, editors, Proceedings of The First Asia-Pacific Conference on Simulated Evolution and Learning, Nov 9-12, 1996, KAIST, Taejon, Korea, 1996, pp. 454–461. 1996.
Akira Onitsuka, Jari Vaario, and Kanji Ueda. Structural formation by enhanced diffusion limited aggregation model. In C. Langton and K. Shimohara, editors, Artificial Life V, pp. 237–243. MIT Press, 1996.
Jari Vaario, Akira Onitsuka, and Katsunori Shimohara. Formation of neural structures. In P. Husbands and I. Harvey, editors, the Proceedings of the Fourth European Conference on Artificial Life. The MIT Press, 1997. (to appear).
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© 1997 Springer-Verlag Berlin Heidelberg
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Vaario, J., Shimohara, K. (1997). Synthesis of developmental and evolutionary modeling of adaptive autonomous agents. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020239
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DOI: https://doi.org/10.1007/BFb0020239
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