Abstract
The paper contains a description of the implementation and performance evaluation of the agent-based population learning algorithm used to train the feed-forward artificial neural networks. The goal of the research was to evaluate efficiency of the agent-based approach and to establish experimentally which different factors representing the A-team structure and topology affect the performance of the analyzed agent-based algorithm. The paper includes a general overview of the JABAT environment used to deploy the ANN training algorithm, a description of different agents employed and their roles, as well as the computational experiment plan and the discussion of the performance evaluation results.
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Czarnowski, I., Jędrzejowicz, P. (2007). Implementation and Performance Evaluation of the Agent-Based Algorithm for ANN Training. In: Nguyen, N.T., Grzech, A., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2007. Lecture Notes in Computer Science(), vol 4496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72830-6_14
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DOI: https://doi.org/10.1007/978-3-540-72830-6_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72829-0
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