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Artificial evolution using neuroevolution of augmenting topologies (NEAT) for kinetics study in diverse viscous mediums

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Abstract

This paper proposes a novel approach for the evolution of artificial creatures which moves in a 3D virtual environment based on the neuroevolution of augmenting topologies (NEAT) algorithm. The NEAT algorithm is used to evolve neural networks that observe the virtual environment and respond to it, by controlling the muscle force of the creature. The genetic algorithm is used to emerge the architecture of creature based on the distance metrics for fitness evaluation. The damaged morphologies of creature are elaborated, and a crossover algorithm is used to control it. Creatures with similar morphological traits are grouped into the same species to limit the complexity of the search space. The motion of virtual creature having 2–3 limbs is recorded at three different angles to check their performance in different types of viscous mediums. The qualitative demonstration of motion of virtual creature represents that improved swimming of virtual creatures is achieved in simulating mediums with viscous drag 1–10 arbitrary unit.

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Acknowledgements

The author acknowledges reviewers for their valuable comments and suggestions.

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Authors and Affiliations

  1. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Sunil Kr. Jha

  2. Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Sunil Kr. Jha

  3. University of Information Science and Technology “St. Paul the Apostle”, 6000, Ohrid, Macedonia

    Filip Josheski

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  1. Sunil Kr. Jha
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  2. Filip Josheski
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Correspondence to Sunil Kr. Jha.

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Jha, S.K., Josheski, F. Artificial evolution using neuroevolution of augmenting topologies (NEAT) for kinetics study in diverse viscous mediums. Neural Comput & Applic 29, 1337–1347 (2018). https://doi.org/10.1007/s00521-016-2664-2

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  • DOI: https://doi.org/10.1007/s00521-016-2664-2

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