- Abstract:
- Realistic planning systems must allow users and computer systems to co-operate and work together using a "mixed initiative" style. Black box or fully automated solutions are not acceptable in many situations. Studies of expert human problem solvers in stressful or critical situations show that they share many of the problem solving methods employed by hirearchical planning methods studied in Artificial Intelligence. But powerful solvers and constraint reasoners can also be of great help in tparts of the planning process. A new more intelligible approach to using AI planning is needed which can use the best "open" styles of planning based on shared plan representations and hierarchical task networks (HTN) and which still allow the use of powerful constraint representations and solvers. I-Plan is a design for a new planning system based on these principles. It is part of the I-X suite of intelligent tools. I-Plan is modular and can be extended via plug-ins of various types. It is intended to be a "lightweight" planning system which can be embedded in other applications. In its simplest form it can provide a small personal planning aid that can be deployed in portable devices and other user-orientated systems to add planning facilities into them. In its more developed forms it will approach the power of generative AI planners such as O-Plan. It provides a framework for including powerful constraint solvers in a framework that is intelligible to the users. I-Plan is grounded in the <I-N-OVA> (Issues, Node, Orderings/Variables/Auxiliary) constraints model used to represent plans and processes. <I-N-OVA> is intended to support a number of different uses: - for automatic and mixed-initiative generation and manipulation of plans and to act as an ontology to underpin such use; - as a common basis for human and system communication about plans; - as a target for principled and reliable acquisition of plans, process models and process product information;
- Copyright:
- 2002 by The University of Edinburgh. All Rights Reserved
- The research sponsors are authorised to reproduce and distribute reprints for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing official policies or endorsements, either express or implied, of the research sponsors or the University of Edinburgh.
- Links To Paper
- No links available
- Bibtex format
- @InProceedings{EDI-INF-RR-0116,
- author = {
Austin Tate
},
- title = {Intelligible AI Planning - Generating Plans Represented as a Set of Constraints},
- book title = {proceedings of ES2000, The Twentieth British Computer Society Special Group on Expert Systems International Conference on Knowledge Based Systems and Applied Artificial Intelligence},
- publisher = {Springer},
- year = 2000,
- month = {Dec},
- pages = {3-16},
- }
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