Abstract
In reinforcement learning exploration phase, it is necessary to introduce a process of trial and error to discover better rewards obtained from environment. To this end, one usually uses the uniform pseudorandom number generator in exploration phase. However, it is known that chaotic source also provides a random-like sequence similar to stochastic source. In this paper we have employed the chaotic generator in the exploration phase of reinforcement learning in a nondeterministic maze problem. We obtained promising results in the so called maze problem.
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Beigi, A., Mozayani, N., Parvin, H. (2011). Chaotic Exploration Generator for Evolutionary Reinforcement Learning Agents in Nondeterministic Environments. In: Dobnikar, A., Lotrič, U., Šter, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2011. Lecture Notes in Computer Science, vol 6594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20267-4_26
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DOI: https://doi.org/10.1007/978-3-642-20267-4_26
Publisher Name: Springer, Berlin, Heidelberg
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