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Emergence of adaptive behaviors for artificial creature using a combined artificial neural network

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Abstract

This study proposes a method to acquire adaptive behavior for artificial creature which has a lot of joints using a combined Artificial Neural Network (ANN). Experiment in this study focuses on artificial fish model, which has a lot of joints, tracking towards a target in the virtual water environment. In order to control motions of joints, a combined ANN is implemented with the model. At first, one ANN is prepared to control specific joints so as to swim basically in response to minimal input information using evolutionary computation in preliminary experiments. And an new network is constructed by combining its network and the other network. In order to acquire complicate behavior for artificial creature, weights of combined ANN are optimized. Experiment result shows the model which has many joints acquire adaptive swimming behavior towards a target by optimizing combined network.

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Authors and Affiliations

  1. Department of Information and Computer Engineering, Gunma National College of Technology, Maebashi, Japan

    Keita Nakamura

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  1. Keita Nakamura
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Correspondence to Keita Nakamura.

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Nakamura, K. Emergence of adaptive behaviors for artificial creature using a combined artificial neural network. Artif Life Robotics 21, 91–97 (2016). https://doi.org/10.1007/s10015-015-0250-9

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  • DOI: https://doi.org/10.1007/s10015-015-0250-9

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