Building Dialogue POMDPs from Expert Dialogues - An end-to-end approach (Paperback, 1st ed. 2016)

This book discusses the Partially Observable Markov Decision Process (POMDP) framework applied in dialogue systems. It presents POMDP as a formal framework to represent uncertainty explicitly while supporting automated policy solving. The authors propose and implement an end-to-end learning approach for dialogue POMDP model components. Starting from scratch, they present the state, the transition model, the observation model and then finally the reward model from unannotated and noisy dialogues. These altogether form a significant set of contributions that can potentially inspire substantial further work. This concise manuscript is written in a simple language, full of illustrative examples, figures, and tables.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Speech Technology
Release date:	February 2016
First published:	2016
Authors:	Hamidreza Chinaei • Brahim Chaib-Draa
Dimensions:	235 x 155 x 7mm (L x W x T)
Format:	Paperback
Pages:	119
Edition:	1st ed. 2016
ISBN-13:	978-3-319-26198-0
Categories:	Books > Language & Literature > Language & linguistics > Computational linguistics Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-26198-3
Barcode:	9783319261980

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