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A Hybrid Adaptive Architecture for Mobile Robots Based on Reactive Behaviours

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Mobile Robots: The Evolutionary Approach

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References

  1. ActivMedia Robotics, Menlo Park, CA. Saphira’s Manual, 2001. Version 8.0a.

    Google Scholar 

  2. Ronald C. Arkin. Behavior-Based Robotics. The MIT Press, Cambridge, MA, 1998.

    Google Scholar 

  3. Esther Luna Colombini and Carlos Henrique Ribeiro. An analysis of feature-based and state-based representations for module-based learning in mobile ro-bots. In Proceedings of the 5th International Conference on Hibrid Intelligent Systems, pages 163-168, Rio de Janeiro, Brazil, November 2005. IEEE Com-puter Society.

    Google Scholar 

  4. Erann Gat. Integrating planning and reacting in a heterogeneous asynchro-nous architecture for controlling real-world mobile robots. In Proceedings of the Tenth National Conference on Artifical Intelligence, pages 809-815, San Jose, California, 1992.

    Google Scholar 

  5. Erann Gat. On three-layer architectures. In D. Kortenkamp, R. Bonasso, and R. Murphy, editors, Artificial Intelligence and Mobile Robots: Case Studies of Successful Robot Systems, pages 195-210. MIT Press, 1998.

    Google Scholar 

  6. Kousuke Inoue, Jun Ota, Tomohiko Katayama, and Tamio Arai. Acceleration of reinforcement learning by a mobile robot using generalized rules. In Proceed-ings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’00), volume 2, pages 885-890, 2000.

    Google Scholar 

  7. Hiroshi Ishiguro, Toshiyuki Kanda, Katumi Kimoto, and Toru Ishida. A robot architecture based on situated modules. In Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’99), volume 3, pages 1617-1624, 1999.

    Google Scholar 

  8. Leslie P. Kaelbling, Michael L. Littman, and Andrew Moore. Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4:237-285, 1996.

    Google Scholar 

  9. Zsolt Kalmár, Csaba Szepesv#x00E1;ri, and Andr#x00E1;s Lörincz Module-based reinforce-ment learning: Experiments with a real robot. Machine Learning, 31(1-3):55-85, April 1998.

    MATH  Google Scholar 

  10. Kian Hsiang Low, Wee Kheng Leow, and Marcelo H. Ang Jr. A hybrid mobile robot architecture with integrated planning and control. In Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent System (AAMAS’02), pages 219-226, Bologna, Italy, 2002.

    Google Scholar 

  11. Maja J. Matarić. Reward functions for accelerated learning. In W. W. Cohen and H. Hirsh, editors, International Conference on Machine Learning, pages 181-189. Morgan Kauffman Publishers, Inc., 1994.

    Google Scholar 

  12. Robin Murphy. Introduction to AI Robotics. The MIT Press, Cambridge, MA, 2000.

    Google Scholar 

  13. Ananth Ranganathan and Sven Koenig. A reactive robot architecture with planning on demand. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’03), volume 2, pages 1462-1468, Las Vegas, California, 2003.

    Google Scholar 

  14. Julio Rosenblatt. DAMN: A distributed architecture for mobile navigation. Journal of Experimental and Theoretical Artificial Intelligence, 9(2/3):339-360, 1997.

    Google Scholar 

  15. Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, New Jersey, 2nd edition, 2003.

    Google Scholar 

  16. Antonio Henrique Pinto Selvatici. AAREACT: Uma arquitetura comporta-mental adaptativa para robôs móveis que integra visão, sonares e odometria. Master’s thesis, Escola Politécnica da USP, São Paulo, Brazil, February 2005.

    Google Scholar 

  17. Richard S. Sutton and Andrew G. Barto. Reinforcement Learning: An Intro-duction. MIT Press, Massachussets, MA, 1998.

    Google Scholar 

  18. Kazunori Terada, Takayuki Nakamura, Hideaki Takeda, and Toyoaki Nishida. A congnitive robot architecture based on tactile and visual information. Advanced Robotics, 13(8):767-777, 2000.

    Google Scholar 

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Selvatici, A.H.P., Costa, A.H.R. (2007). A Hybrid Adaptive Architecture for Mobile Robots Based on Reactive Behaviours. In: Nedjah, N., Coelho, L.d.S., Mourelle, L.d.M. (eds) Mobile Robots: The Evolutionary Approach. Studies in Computational Intelligence, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49720-2_8

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  • DOI: https://doi.org/10.1007/978-3-540-49720-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

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