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Deep-Sarsa: A Reinforcement Learning Algorithm For Autonomous Navigation

Author

Listed:
  • M. ANDRECUT

    (Department of Physics, University of Lethbridge, 4401 University Drive, Lethbridge, Alberta, T1K 3M4, Canada)

  • M. K. ALI

    (Department of Physics, University of Lethbridge, 4401 University Drive, Lethbridge, Alberta, T1K 3M4, Canada)

Abstract

In this paper we discuss the application of reinforcement learning algorithms to the problem of autonomous robot navigation. We show that the autonomous navigation using the standard delayed reinforcement learning algorithms is an ill posed problem and we present a more efficient algorithm for which the convergence speed is greatly improved. The proposed algorithm (Deep-Sarsa) is based on a combination between the Depth-First Search (a graph searching algorithm) and Sarsa (a delayed reinforcement learning algorithm).

Suggested Citation

  • M. Andrecut & M. K. Ali, 2001. "Deep-Sarsa: A Reinforcement Learning Algorithm For Autonomous Navigation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 12(10), pages 1513-1523.
    • Handle: RePEc:wsi:ijmpcx:v:12:y:2001:i:10:n:s0129183101002851
    DOI: 10.1142/S0129183101002851
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