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Semantic Support for Visualisation in Collaborative AI Planning

By N Lino, Austin Tate and Y-H Chen-Burger

Abstract

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In the last decades, many advances have been made in intelligent planning systems. Significant improvements related to core problems, providing faster search algorithms and shortest plans have been proposed. However, there is a lack in researches\ud allowing a better support for a proper use\ud and interaction with planners, where, for instance, visualization can play an important role.This work proposes a general framework for visualisation of planning information using an approach based on semantic modelling. It intends to enhance the notion of knowledge-based planning applying it to other aspects of planning, such as visualisation. The approach consists in an integrated\ud ontology set and reasoning mechanism for\ud multi-modality visualisation destined to collaborative planning environments. This framework will permit organizing and modelling the domain from the visualisation perspective, and give a tailored support for presentation of information

Topics: intelligent planning systems, artificial intelligence, semantic modelling, collaborative planning, computer science, informatics, Artificial Intelligence Applications Institute
Publisher: International Conference on Automated Planning and Scheduling
Year: 2005
OAI identifier: oai:www.era.lib.ed.ac.uk:1842/2269

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