DEEP-SARSA: A REINFORCEMENT LEARNING ALGORITHM FOR AUTONOMOUS NAVIGATION

M. Andrecut () and M. K. Ali ()
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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

International Journal of Modern Physics C (IJMPC), 2001, vol. 12, issue 10, 1513-1523

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).

Keywords: Reinforcement learning; autonomous navigation (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1142/S0129183101002851

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