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Application of Coarse-Coding Techniques for Evolvable Multirobot Controllers

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Computational Intelligence in Optimization

Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 7))

Abstract

Robots, in their most general embodiment, can be complex systems trying to negotiate and manipulate an unstructured environment. They ideally require an ‘intelligence’ that reflects our own. Artificial evolutionary algorithms are often used to generate a high-level controller for single and multi robot scenarios. But evolutionary algorithms, for all their advantages, can be very computationally intensive. It is therefore very desirable to minimize the number of generations required for a solution. In this chapter, we incorporate the Artificial Neural Tissue (ANT) approach for robot control from previous work with a novel Sensory Coarse Coding (SCC) model. This model is able to exploit regularity in the sensor data of the environment. Determining how the sensor suite of a robot should be configured and utilized is critical for the robot’s operation. Much as nature evolves body and brain simultaneously, we should expect improved performance resulting from artificially evolving the controller and sensor configuration in unison. Simulation results on an example task, resource gathering, show that the ANT+SCC system is capable of finding fitter solutions in fewer generations. We also report on hardware experiments for the same task that show complex behaviors emerging through self-organized task decomposition.

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Author information

Authors and Affiliations

  1. Mechanical Engineering Dept., Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, USA, 02139

    Jekanthan Thangavelautham

  2. Institute for Aerospace Studies, University of Toronto, 4925 Dufferin St., Toronto, Canada, M3H5T6

    Paul Grouchy & Gabriele M. T. D’Eleuterio

Authors
  1. Jekanthan Thangavelautham
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  2. Paul Grouchy
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  3. Gabriele M. T. D’Eleuterio
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering and Science-Faculty of Engineering, Kyoto University, Yoshida-honmachi,Sakyo-Ku, 606-8501, Kyoto, Japan

    Yoel Tenne

  2. Advanced Technology Centre, Rolls-Royce Singapore Pte Ltd, 50 Nanyang Avenue, Block N2,Level B3C,Unit 05-08, 639798, Singapore

    Chi-Keong Goh

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Thangavelautham, J., Grouchy, P., D’Eleuterio, G.M.T. (2010). Application of Coarse-Coding Techniques for Evolvable Multirobot Controllers. In: Tenne, Y., Goh, CK. (eds) Computational Intelligence in Optimization. Adaptation, Learning, and Optimization, vol 7. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12775-5_16

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  • DOI: https://doi.org/10.1007/978-3-642-12775-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12774-8

  • Online ISBN: 978-3-642-12775-5

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