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Scaling POMDPs for Dialog Management with Composite Summary Point-based Value Iteration (CSPBVI (2006)
| Content Provider | CiteSeerX |
|---|---|
| Author | Williams, Jason D. |
| Description | 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). CSP-BVI 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. |
| File Format | |
| Language | English |
| Publisher Date | 2006-01-01 |
| Publisher Institution | CSPBVI),” in AAAI Workshop on Statistical and Empirical Approaches for Spoken Dialogue Systems |
| Access Restriction | Open |
| Subject Keyword | User Model Estimation Spoken Dialog System Slot-filling Pomdp-based Dialog Manager Many Slot Pomdp-based Dialog Manager Composite Point-based Value Iteration Observable Markov Decision Process Local Pomdp Policy Dialog Management Heuristic Chooses Performance Gain Composite Summary Point-based Value Iteration Novel Technique Great Promise Baseline Technique Important Scalability Issue Dialog Simulation Show |
| Content Type | Text |
| Resource Type | Article |
