Most existing commercial goal-oriented chatbots are diagram-based; i.e., they follow a rigid dialog flow to fill the slot values needed to achieve a user's goal. Diagram-based chatbots are predictable, thus their adoption in commercial settings; however, their lack of flexibility may cause many users to leave the conversation before achieving their goal. On the other hand, state-of-the-art research chatbots use Reinforcement Learning (RL) to generate flexible dialog policies. However, such chatbots can be unpredictable, may violate the intended business constraints, and require large training datasets to produce a mature policy. We propose a framework that achieves a middle ground between the diagram-based and RL-based chatbots: we constrain the space of possible chatbot responses using a novel structure, the chatbot dependency graph, and use RL to dynamically select the best valid responses. Dependency graphs are directed graphs that conveniently express a chatbot's logic by defining the dependencies among slots: all valid dialog flows are encapsulated in one dependency graph. Our experiments in several domains show that our framework quickly adapts to user characteristics and achieves up to 23.77% improved success rate compared to a state-of-the-art RL model.
|Title of host publication||Proceedings - 2021 IEEE 15th International Conference on Semantic Computing, ICSC 2021|
|Number of pages||8|
|State||Published - Jan 2021|
|Event||15th IEEE International Conference on Semantic Computing, ICSC 2021 - Virtual, Laguna Hills, United States|
Duration: Jan 27 2021 → Jan 29 2021
|Name||Proceedings - 2021 IEEE 15th International Conference on Semantic Computing, ICSC 2021|
|Conference||15th IEEE International Conference on Semantic Computing, ICSC 2021|
|City||Virtual, Laguna Hills|
|Period||1/27/21 → 1/29/21|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This work was supported by NSF grants IIS-1619463, IIS-1838222, and IIS-1901379.
© 2021 IEEE.
- Dialog policy
- Dialog systems
- Goal oriented chatbots
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Decision Sciences (miscellaneous)