Abstract
This paper describes architecture of an artificial intelligence system based on the Elman neural network. Simple training algorithms and neural network models are not able to solve such a complex problem as movements in the conditions of an independent game world environment, so a combination of a base neural network training algorithm and Q-learning agent approach is used as part of a player behavior control model. The paper also includes results of experiments with different values of model and game world characteristics and shows efficiency of the described approach.
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Kuznetsov, D., Plotnikova, N. (2019). Aspects of Using Elman Neural Network for Controlling Game Object Movements in Simplified Game World. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_38
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DOI: https://doi.org/10.1007/978-3-319-91189-2_38
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