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L. C. Barid and A. W. Moore. Gradient descent for general reinforcement learning. In Proceedings of the International Conference on Advances in neural information processing systems II, pages 968-974. MIT Press, 1999.
G. Z. Grudic, V. Kumar, and L. Ungar. Using policy gradient reinfrocement learning on autonmous robot controllers. In Proceedings of IEEE/RSJ Interna-tional Conference on Intelligent Robots and Systems, pages 406-411, Las Vagas, Navada, USA, Oct 2003.
G. Hornby, S. Takamura, J. Yokono, O. Hanagata, T. Yamamoto, and M. Fujita. Evolving robust gaits with AIBO. In Proceedings of IEEE International Con-ference on Robotics and Automation, pages 3040-3045, 2000.
N. Kohl and P. Stone. Policy gradient reinforcement learning for fast quadrupedal locomotion. In Proceedings of IEEE International Conference on Robotics and Automation, volume 3, pages 2619-2624, May 2004.
J. Liu and H. Hu. Building a 3d simulator for autonomous navigation of robotic fishes. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 613-618, Sendai, Japan, Oct 2004.
J. Liu and H. Hu. Mimicry of sharp turning behaviours in a robotic fish. In Pro-ceedings of IEEE International Conference on Robotics and Automation, pages 3329-3334, Barcelona, Spain, April 2005.
L. Peshkin, K. Kim, N. Meuleau, and L. Kaelbling. Learning to cooperate via policy search. In Proceedings of the 6th International Conference on Uncertainty in Artificial Intelligence, pages 307-314, 2000.
C. J. C. H. Watkins. Learning from Delayed Rewards. PhD thesis, Cambridge University, 1989.
R. J. William. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine learning, 8:229-256, 1992.
R. Zhang and P. Vadakkepat. An evolutionary algorithm for trajectory based gait generation of biped robot. In Proceedings of the International Conference on Computational Intelligence, Robotics and Autonomous Systems, Singapore, 2003.
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Liu, J., Parker, L.E., Madhavan, R. (2007). Reinforcement Learning for Autonomous Robotic Fish. 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_6
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