Abstract
In this paper, we investigate the knowledge acquisition and the learning ability of an agent in a three-dimensional (3D) environment using data mining techniques. We apply three data mining techniques: naïve Bayes, decision tree and apriori; to a human-controlled navigation and then investigate the characteristic of knowledge discovered from each of these techniques. The results shows that the agent is able to learn to navigate automatically in the environment but with different outcomes and limitations.
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Haji Mohd Sani, N., Phon-Amnuaisuk, S., Au, T.W., Tan, E.L. (2016). Learning to Navigate in a 3D Environment. In: Sombattheera, C., Stolzenburg, F., Lin, F., Nayak, A. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2016. Lecture Notes in Computer Science(), vol 10053. Springer, Cham. https://doi.org/10.1007/978-3-319-49397-8_23
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DOI: https://doi.org/10.1007/978-3-319-49397-8_23
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