Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
The Knowledge Engineering Review
Learning more effective dialogue strategies using limited dialogue move features
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
Testing the performance of spoken dialogue systems by means of an artificially simulated user
Artificial Intelligence Review
Being Old Doesn’t Mean Acting Old: How Older Users Interact with Spoken Dialog Systems
ACM Transactions on Accessible Computing (TACCESS)
Simulating the behaviour of older versus younger users when interacting with spoken dialogue systems
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Natural language generation as planning under uncertainty for spoken dialogue systems
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Reducing working memory load in spoken dialogue systems
Interacting with Computers
Hybrid approach to user intention modeling for dialog simulation
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Learning culture-specific dialogue models from non culture-specific data
UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: users diversity - Volume Part II
Reinforcement learning of question-answering dialogue policies for virtual museum guides
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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Older adults are a challenging user group because their behaviour can be highly variable. To the best of our knowledge, this is the first study where dialogue strategies are learned and evaluated with both simulated younger users and simulated older users. The simulated users were derived from a corpus of interactions with a strict system-initiative spoken dialogue system (SDS). Learning from simulated younger users leads to a policy which is close to one of the dialogue strategies of the underlying SDS, while the simulated older users allow us to learn more flexible dialogue strategies that accommodate mixed initiative. We conclude that simulated users are a useful technique for modelling the behaviour of new user groups.