Abstract
In the following Chapter we provide a “proof-of-concept” that RL outperforms hand-coded strategies which are manually tuned to the same reward function. We also show this for a wide range of application scenarios. We use simulation-based optimisation, i.e. we adapt different strategies to different simulated environments.
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© 2011 Springer-Verlag Berlin Heidelberg
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Rieser, V., Lemon, O. (2011). Proof-of-Concept: Information Seeking Strategies. In: Reinforcement Learning for Adaptive Dialogue Systems. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24942-6_4
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DOI: https://doi.org/10.1007/978-3-642-24942-6_4
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24941-9
Online ISBN: 978-3-642-24942-6
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