T4. Learning Techniques in Planning

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Abstract

This tutorial aims to provide an overview of learning techniques for planning--an area with significant past as well as a substantial current interest. From planning perspective, learning techniques can be seen as (i) a way to "speed-up" planners or (ii) as a way to reduce domain-modeling burden. Early interest in this area was driven almost exclusively by the first, while the recent resurgence is motivated by the second consideration. From the learning perspective, focus on planning necessitates a welcome diversion from the dominant tabula-rasa paradigms. Specifically, it encourages handling relational and first order representations, and foregrounds the need for knowledge-intensive learning techniques (such as explanation-based and relevance-based learning).

We will survey both the history as well as promising current trends, and make connections to DARPA Integrated Learning program, Model-lite planning.