Abstract
This paper explains an architecture for a BDI agent that can learn based on its own experience. The learning is conducted through explicit procedural knowledge or plans in a goal-directed manner. The learning is described by encoding abductions within the deliberation processes. With this model, the agent is capable of modifying its own plans on the run. We demonstrate that by abducing some complex structures of plan, the agent can also acquire complex structures of knowledge about its interaction with the environment.
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Subagdja, B., Rahwan, I., Sonenberg, L. (2006). Learning as Abductive Deliberations. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_4
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DOI: https://doi.org/10.1007/978-3-540-36668-3_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36667-6
Online ISBN: 978-3-540-36668-3
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