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Table of contents(6 chapters)
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.
Authors and Affiliations
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, Department of Computer Science, University of Oxford, Oxford, United Kingdom
Gerardo I. Simari
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Brooklyn College, Dept. Computer & Information Science, City University of New York, Brooklyn, USA
Simon D. Parsons
Bibliographic Information
Book Title: Markov Decision Processes and the Belief-Desire-Intention Model
Book Subtitle: Bridging the Gap for Autonomous Agents
Authors: Gerardo I. Simari, Simon D. Parsons
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-1-4614-1472-8
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2011
Softcover ISBN: 978-1-4614-1471-1
eBook ISBN: 978-1-4614-1472-8
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: VIII, 63