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Markov Decision Processes and the Belief-Desire-Intention Model (Record no. 21247)

000 -LEADER
fixed length control field 02668nam a22004455i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310151113.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110915s2011 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461414728
978-1-4614-1472-8
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
Classification number TJ210.2-211.495
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
264 #1 -
-- New York, NY :
-- Springer New York,
-- 2011.
912 ## -
-- ZDB-2-SCS
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Simari, Gerardo I.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Markov Decision Processes and the Belief-Desire-Intention Model
Medium [electronic resource] :
Remainder of title Bridging the Gap for Autonomous Agents /
Statement of responsibility, etc by Gerardo I. Simari, Simon D. Parsons.
300 ## - PHYSICAL DESCRIPTION
Extent VIII, 63p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title SpringerBriefs in Computer Science,
International Standard Serial Number 2191-5768
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Preliminary Concepts -- An Empirical Comparison of Models -- A Theoretical Comparison of Models -- Related Work. Conclusions, Limitations, and Future Directions.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Artificial intelligence.
Topical term or geographic name as entry element Computer simulation.
Topical term or geographic name as entry element Computer Science.
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
Topical term or geographic name as entry element Simulation and Modeling.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Parsons, Simon D.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781461414711
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-1472-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-08AUM Main Library2014-04-08 2014-04-08 E-Book   AUM Main Library006.3

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