Optimising a handcrafted dialogue system design

By Romain Laroche, Ghislain Putois, P. Bretier. 2010

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Safe Policy Improvement with Baseline Bootstrapping (2017, background): “This scenario is typically encountered when a policy is trained in a simulator and then run in its real environment, for instance in Transfer RL (Taylor & Stone, 2009); or when a system is designed with expert knowledge and then optimized, for example in Dialogue applications (Laroche et al., 2010).”
Policy Networks with Two-Stage Training for Dialogue Systems (2016, methodology): “The statistical optimization of dialogue management in dialogue systems through Reinforcement Learning (RL) has been an active thread of research for more than two decades (Levin et al., 1997; Lemon and Pietquin, 2007; Laroche et al., 2010; Gaˇsi´c et al., 2012; Daubigney et al., 2012).”