Learning Action Models for Planning: An Overview of the Hedlamp Project

Thomas Leo McCluskey, Lukas Chrpa, Austin Tate, Gerhard Wickler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hedlamp is a UK EPSRC grant funded research project in which we aim to tackle challenges with knowledge engineering of automated planning techniques when applied to real applications. Normally, successful deployment of planning technology relies on groups of planning experts encoding detailed domain models and investing large amounts of time maintaining them.We are developing a high level, application-oriented knowledge engineering framework usable by application developers who want to experiment with the potential of AI Planning,while encoding a precise domain model of some valuable application area. We are developing tools and theory for the framework which support knowledge acquisition, validation and operationality of the domain model. In particular, this project aims to explore the opportunities of applying model translation, adaptation and reformulation techniques to improve the model’s quality, and that of the planning function of which it is a part.In this paper we outline the main areas that Hedlamp has addressed,and overview an automated knowledge acquisition technique that has been tested with real industrial process data.
Original languageEnglish
Title of host publicationPlanSIG 2015/16
Number of pages6
Publication statusPublished - 2016

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