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Statistical Dialogue Management using Intention Dependency Graph
2013
International Joint Conference on Natural Language Processing
We present a method of statistical dialogue management using a directed intention dependency graph (IDG) in a partially observable Markov decision process (POMDP) framework. The transition probabilities in this model involve information derived from a hierarchical graph of intentions. In this way, we combine the deterministic graph structure of a conventional rule-based system with a statistical dialogue framework. The IDG also provides a reasonable constraint on a user simulation model, which
dblp:conf/ijcnlp/YoshinoWRH13
fatcat:m5ae7w6ubvab3hgfwku2ditcgi