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Scaling POMDPs for dialog management with composite summary point-based value iteration (CSPBVI)

Williams, JD and Young, S (2006) Scaling POMDPs for dialog management with composite summary point-based value iteration (CSPBVI). AAAI Workshop - Technical Report, WS-06-. pp. 37-42.

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Abstract

Although partially observable Markov decision processes (POMDPs) have shown great promise as a framework for dialog management in spoken dialog systems, important scalability issues remain. This paper tackles the problem of scaling slot-filling POMDP-based dialog managers to many slots with a novel technique called composite point-based value iteration (CSPBVI). CSPBVI creates a "local" POMDP policy for each slot; at runtime, each slot nominates an action and a heuristic chooses which action to take. Experiments in dialog simulation show that CSPBVI successfully scales POMDP-based dialog managers without compromising performance gains over baseline techniques and preserving robustness to errors in user model estimation. Copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 12:05
Last Modified: 27 Nov 2014 19:21
DOI: