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Towards a Zero-Data, Controllable, Adaptive Dialog System
March 27, 2024, 4:42 a.m. | Dirk V\"ath, Lindsey Vanderlyn, Ngoc Thang Vu
cs.LG updates on arXiv.org arxiv.org
Abstract: Conversational Tree Search (V\"ath et al., 2023) is a recent approach to controllable dialog systems, where domain experts shape the behavior of a Reinforcement Learning agent through a dialog tree. The agent learns to efficiently navigate this tree, while adapting to information needs, e.g., domain familiarity, of different users. However, the need for additional training data hinders deployment in new domains. To address this, we explore approaches to generate this data directly from dialog trees. …
abstract agent arxiv behavior conversational cs.ai cs.cl cs.lg data dialog domain domain experts experts information reinforcement reinforcement learning search systems through tree type
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