Titlebook: Artificial Intelligence XXXIV; 37th SGAI Internatio Max Bramer,Miltos Petridis Conference proceedings 2017 Springer International Publishin

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https://doi.org/10.1007/978-1-4842-3330-6wer Line Wars from Warcraft III, Blizzard Entertainment. Further, as a proof of concept that the environment can harbor Deep Reinforcement algorithms, we propose and apply a Deep Q-Reinforcement architecture. The architecture simplifies the state space so that it is applicable to Q-learning, and in

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The Platform Logging API and Service, the other uses dynamic rule term boundaries. Both versions have been compared empirically against Prism on 11 datasets using various evaluation metrics. The results show that in most cases both versions of G-Prism, especially G-Prism with dynamic boundaries, achieve a better classification performa

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A Learning Automata Local Contribution Sampling Applied to Hydropower Production Optimisationrations. Our results also demonstrate that local directed feedback provides significantly faster convergence than global feedback. These results lead us to conclude that LA LCS holds great promise for solving complex, non-linear and stochastic optimisation problems, opening up for improved performan

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Artificial Intelligence XXXIV978-3-319-71078-5Series ISSN 0302-9743 Series E-ISSN 1611-3349