Epsilon-Subjective Equivalence of Models for Interactive Dynamic Influence Diagrams

Interactive dynamic influence diagrams (I-DID) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning behavio...

Full description

Saved in:
Bibliographic Details
Published in2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Vol. 2; pp. 165 - 172
Main Authors Doshi, Prashant, Chandrasekaran, Muthukumaran, Zeng, Yifeng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
agent models
Computational modeling
Computer science
Decision making
dynamic influence diagrams
Graphical models
History
multiagent settings
Predictive models
Probability distribution
Semantics
Time complexity
Online AccessGet full text
ISBN9781424484829
1424484820
DOI10.1109/WI-IAT.2010.74

Cover

More Information
Summary:Interactive dynamic influence diagrams (I-DID) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning behaviorally equivalent models is one way toward minimizing the model set. We seek to further reduce the complexity by additionally pruning models that are approximately subjectively equivalent. Toward this, we define subjective equivalence in terms of the distribution over the subject agent's future action-observation paths, and introduce the notion of epsilon-subjective equivalence. We present a new approximation technique that reduces the candidate model space by removing models that are epsilon-subjectively equivalent with representative ones.
ISBN:9781424484829
1424484820
DOI:10.1109/WI-IAT.2010.74