LIHLITH - Learning to Interact with Humans by Lifelong Interaction with Humans
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The LIHLITH project is a ?fundamental pilot research project
which introduces a new lifelong learning framework for the
interaction of humans and machines on specific 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.
The research will be evaluated on publicly available benchmarks to
allow comparison with other approaches in the state of the art.
When possible, systems will participate in international
comparative/competitive evaluations such as WOCHAT or SemEval.
LIHLITH project will also develop and deliver evaluation protocols
and benchmarks to allow public comparison and reproducibility based
on crowdsourcing. The industrial partner will transfer the research
into technology, applying the lessons learnt to the development of
?chatbots for customer support.?
LIHLITH will rely on recent advance in multiple research disciplines, including, ?natural language processing, knowledge induction, reinforcement learning, deep learning, and lifelong learning?.