Markov Decision Processes and the Belief-Desire-Intention Model

Bridging the Gap for Autonomous Agents

  • Gerardo I. Simari
  • Simon D. Parsons

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Gerardo I. Simari, Simon D. Parsons
    Pages 1-2
  3. Gerardo I. Simari, Simon D. Parsons
    Pages 3-9
  4. Gerardo I. Simari, Simon D. Parsons
    Pages 11-25
  5. Gerardo I. Simari, Simon D. Parsons
    Pages 27-48
  6. Gerardo I. Simari, Simon D. Parsons
    Pages 49-53
  7. Gerardo I. Simari, Simon D. Parsons
    Pages 55-56
  8. Back Matter
    Pages 57-63

About this book


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.


Agent Architectures Autonomous Agents Brief-Desire-Intention Markov Decision Process Relationship between models

Authors and affiliations

  • Gerardo I. Simari
    • 1
  • Simon D. Parsons
    • 2
  1. 1., Department of Computer ScienceUniversity of OxfordOxfordUnited Kingdom
  2. 2.Brooklyn College, Dept. Computer & Information ScienceCity University of New YorkBrooklynUSA

Bibliographic information