Learning to Interact with Humans by Lifelong Interaction with Humans
(2017 - 2020)
LIHLITH introduces a new lifelong learning framework for the interaction of humans and machines on specific domains with the aim of improving the quality of existing dialogue systems and lowering the cost of deployment in new domains.
A Lifelong Learning system learns different tasks sequentially, over time, getting better at solving future related tasks based on past experience. LIHLITH will focus on human-computer dialogue, where each dialogue experience is used by the system to learn to better interact, based on the success (or failure) of previous interactions. The key insight is that the dialogue will be designed to produce a reward, allowing the chatbot system to know whether the interaction was successful or not. The reward will be used to train the domain and dialogue management modules of the chatbot, improving the performance, and reducing the development cost, both on a single target domain but specially when moving to new domains.
LIHLITH project will also develop and deliver evaluation protocols and benchmarks to allow public comparison and reproducibility based on crowdsourcing.
Organization: Ministerio de Economía, Industria y Competitividad (Chistera)
Main researcher: Eneko Agirre
Participants: Basi Sierra
Eneko Agirre, Josu Goikoetxea, Oier Lopez de Lacalle , Arantxa Otegi, Olatz Perez de Viñaspre, German Rigau