Markov Decision Processes and the Belief-Desire-Intention Model: Bridging the Gap for Autonomous Agents (SpringerBriefs in Computer Science)

by Gerardo I. Simari and Simon D. Parsons

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In this work, we provide a treatment of the relationship between two models that have been widely used in the implementation of autonomous agents: the Belief DesireIntention (BDI) model and Markov Decision Processes (MDPs). We start with an informal description of the relationship, identifying the common features of the two approaches and the differences between them. Then we hone our understanding of these differences through an empirical analysis of the performance of both models on the TileWorld testbed. This allows us to show that even though the MDP model displays consistently better behavior than the BDI model for small worlds, this is not the case when the world becomes large and the MDP model cannot be solved exactly. Finally we present a theoretical analysis of the relationship between the two approaches, identifying mappings that allow us to extract a set of intentions from a policy (a solution to an MDP), and to extract a policy from a set of intentions.

  • ISBN13 9781461414711
  • Publish Date 16 September 2011 (first published 1 January 2011)
  • Publish Status Active
  • Publish Country US
  • Imprint Springer-Verlag New York Inc.
  • Edition 2011
  • Format Paperback
  • Pages 63
  • Language English