A strategy learning model for autonomous agents based on classification
Bartłomiej Śnieżyński (2015)
International Journal of Applied Mathematics and Computer Science
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In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for...