Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
Enabling technology for multilingual natural language generation: the KPML development environment
Natural Language Engineering
Building applied natural language generation systems
Natural Language Engineering
Generation that exploits corpus-based statistical knowledge
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
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
Learning lexical alignment policies for generating referring expressions in spoken dialogue systems
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
Evaluation of a hierarchical reinforcement learning spoken dialogue system
Computer Speech and Language
Hierarchical reinforcement learning with the MAXQ value function decomposition
Journal of Artificial Intelligence Research
Adaptive referring expression generation in spoken dialogue systems: evaluation with real users
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Spatially-aware dialogue control using hierarchical reinforcement learning
ACM Transactions on Speech and Language Processing (TSLP)
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Optimising natural language generation decision making for situated dialogue
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Collective intelligence as a source for machine learning self-supervision
Proceedings of the 4th International Workshop on Web Intelligence & Communities
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We present a novel approach to natural language generation (NLG) that applies hierarchical reinforcement learning to text generation in the wayfinding domain. Our approach aims to optimise the integration of NLG tasks that are inherently different in nature, such as decisions of content selection, text structure, user modelling, referring expression generation (REG), and surface realisation. It also aims to capture existing interdependencies between these areas. We apply hierarchical reinforcement learning to learn a generation policy that captures these interdependencies, and that can be transferred to other NLG tasks. Our experimental results---in a simulated environment---show that the learnt wayfinding policy outperforms a baseline policy that takes reasonable actions but without optimization.