Klaus-Peter Engelbrecht


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Evaluating Persuasion Strategies and Deep Reinforcement Learning methods for Negotiation Dialogue agents
Simon Keizer | Markus Guhe | Heriberto Cuayáhuitl | Ioannis Efstathiou | Klaus-Peter Engelbrecht | Mihai Dobre | Alex Lascarides | Oliver Lemon
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

In this paper we present a comparative evaluation of various negotiation strategies within an online version of the game “Settlers of Catan”. The comparison is based on human subjects playing games against artificial game-playing agents (‘bots’) which implement different negotiation dialogue strategies, using a chat dialogue interface to negotiate trades. Our results suggest that a negotiation strategy that uses persuasion, as well as a strategy that is trained from data using Deep Reinforcement Learning, both lead to an improved win rate against humans, compared to previous rule-based and supervised learning baseline dialogue negotiators.


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Position Paper: Towards Standardized Metrics and Tools for Spoken and Multimodal Dialog System Evaluation
Sebastian Möller | Klaus-Peter Engelbrecht | Florian Kretzschmar | Stefan Schmidt | Benjamin Weiss
NAACL-HLT Workshop on Future directions and needs in the Spoken Dialog Community: Tools and Data (SDCTD 2012)


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Modeling User Satisfaction with Hidden Markov Models
Klaus-Peter Engelbrecht | Florian Gödde | Felix Hartard | Hamed Ketabdar | Sebastian Möller
Proceedings of the SIGDIAL 2009 Conference


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Pragmatic Usage of Linear Regression Models for the Prediction of User Judgments
Klaus-Peter Engelbrecht | Sebastian Möller
Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue