DMCA
Approximate Solutions of Interactive Dynamic Influence Diagrams Using ǫ-Behavioral Equivalence
| Citations: | 2 - 2 self |
BibTeX
@MISC{C_approximatesolutions,
author = {Muthukumaran C and Prashant Doshi and Yifeng Zeng},
title = {Approximate Solutions of Interactive Dynamic Influence Diagrams Using ǫ-Behavioral Equivalence},
year = {}
}
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Abstract
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 the behaviorally equivalent models is one way toward identifying a minimal model set. We further reduce the complexity by pruning models that are approximately behaviorally equivalent. Toward this, we redefine behavioral equivalence in terms of the distribution over the subject agent’s future action-observation paths, and introduce the notion of ǫ-behavioral equivalence. We present a new approximation method that reduces the candidate models by pruning models that are ǫ-behaviorally equivalent with representative ones. 1
Keyphrases
approximate solution behavioral equivalence candidate model subject agent future action-observation path sequential decision making graphical model new approximation method i-dids face uncertain setting representative one equivalent model interactive dynamic influence diagram minimal model
