Reinforcement Learning
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Planning and Acting under Uncertainty: A New Model for Spoken Dialogue System
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
PARADISE: a framework for evaluating spoken dialogue agents
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Learning optimal dialogue strategies: a case study of a spoken dialogue agent for email
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic optimization of dialogue management
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Spoken dialogue management using probabilistic reasoning
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Fast reinforcement learning of dialog strategies
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Journal of Artificial Intelligence Research
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
Training a Dialogue Act Tagger for human-human and human-computer travel dialogues
SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
The Knowledge Engineering Review
Error handling in the RavenClaw dialog management framework
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Learning mixed initiative dialog strategies by using reinforcement learning on both conversants
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
A statistical approach to spoken dialog systems design and evaluation
Speech Communication
Evaluating user simulations with the Cramér-von Mises divergence
Speech Communication
Hybrid reinforcement/supervised learning of dialogue policies from fixed data sets
Computational Linguistics
Learning effective and engaging strategies for advice-giving human-machine dialogue
Natural Language Engineering
Training a real-world POMDP-based dialogue system
NAACL-HLT-Dialog '07 Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies
An Online Algorithm for Applying Reinforcement Learning to Handle Ambiguity in Spoken Dialogues
TAMC '09 Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation
Evaluation of a hierarchical reinforcement learning spoken dialogue system
Computer Speech and Language
Reinforcement learning for mapping instructions to actions
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Using word-sense disambiguation methods to classify web queries by intent
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
A comparison between dialog corpora acquired with real and simulated users
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
The Knowledge Engineering Review
Human robot interactions: towards the implementation of adaptive strategies for robust communication
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
A statistical user simulation technique for the improvement of a spoken dialog system
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Using reinforcement learning to create communication channel management strategies for diverse users
SLPAT '10 Proceedings of the NAACL HLT 2010 Workshop on Speech and Language Processing for Assistive Technologies
Grammatical error simulation for computer-assisted language learning
Knowledge-Based Systems
Learning automata-based approach to learn dialogue policies in large state space
International Journal of Intelligent Information and Database Systems
Journal of Ambient Intelligence and Smart Environments - A software engineering perspective on smart applications for AmI
Generative goal-driven user simulation for dialog management
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Inverse reinforcement learning for interactive systems
Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication
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This paper describes a method for automatic design of human-computer dialogue strategies by means of reinforcement learning, using a dialogue simulation tool to model the user behaviour and system recognition performance. To the authors' knowledge this is the first application of a detailed simulation tool to this problem. The simulation tool is trained on a corpus of real user data. Compared to direct state transition modelling, it has the major advantage that different state space representations can be studied without collecting more training data. We applied Q-learning with eligibility traces to obtain policies for a telephone-based cinema information system, comparing the effect of different state space representations and evaluation functions. The policies outperformed handcrafted policies that operated in the same restricted state space, and gave performance similar to the original design that had been through several iterations of manual refinement.