Learning as Abductive Deliberations

  • Budhitama Subagdja
  • Iyad Rahwan
  • Liz Sonenberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4099)


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.


Plan Body Belief State Composite Action Learn Plan Deliberation Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Budhitama Subagdja
    • 1
  • Iyad Rahwan
    • 2
  • Liz Sonenberg
    • 1
  1. 1.Department of Information SystemsUniversity of Melbourne 
  2. 2.Institute of InformaticsThe British University in Dubai, (Fellow) School of Informatics, University of EdinburghUK

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