Abstract
This paper introduces and tests Action Planning mechanism in the Anticipatory Classifier System ACS2. Action Planning implies goal-directed learning and bidirectional search to strengthen reliable classifiers. It is shown that it can speed up the process of gaining knowledge about the learned environment. Experiments were performed over three environments (Hand-Eye, Maze and Taxi) extended with custom goal-generator functions.
The work was supported by statutory grant of the Wrocław University of Science and Technology, Poland.
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Unold, O., Rogula, E., Kozłowski, N. (2020). Introducing Action Planning to the Anticipatory Classifier System ACS2. In: Burduk, R., Kurzynski, M., Wozniak, M. (eds) Progress in Computer Recognition Systems. CORES 2019. Advances in Intelligent Systems and Computing, vol 977. Springer, Cham. https://doi.org/10.1007/978-3-030-19738-4_27
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DOI: https://doi.org/10.1007/978-3-030-19738-4_27
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