Steve Chien & Brian Drabble
Automated planning is the generation of a sequence of actions (potentially to a level that can be executed) to achieve some desired world state while obeying the constraints of the domain. Planning systems can be used to automate procedure generation problems in a wide range of areas such as: data analysis, distribution logistics, systems engineering, process flow, crisis response, and space payload operations.
Automated planning technology can reduce operations costs, decrease manual errors and thus increase consistency, and reduce dependency on key personnel. This tutorial will cover key issues, problems, and approaches central in fielding automated planning systems with lessons and solutions drawn from the presentersŐ experience in fielding planning systems for science data analysis, spacecraft payload checkout, and communications antenna operations.
This tutorial will cover the basic concepts in domain-independent artificial intelligence planning including: search, representing planning knowledge, plan and state space planning, operator-based planning and hierarchical task network planning. Advanced concepts such as integrated planning and scheduling, decision theoretic planning, and mixed initiative planning will also be briefly discussed. Important questions relevant to planning will be covered in the tutorial such as:
Prerequisite knowledge:
Knowledge of basic concepts from artificial intelligence will be
presumed: search, expert systems, logic-like
representations. Familiarity with some planning and scheduling
systems, basic search strategies, reactive systems, and/or scripting
languages would be helpful but not essential.
Dr. Steve Chien is Technical Group Supervisor of the Artificial Intelligence Group at the Jet Propulsion Laboratory, California Institute of Technology, where he leads efforts in automated planning and scheduling. His current projects include basic research and deployment of planning systems for automated science analysis, spacecraft mission planning, spacecraft design, maintenance of space transportation systems, and Deep Space Network Antenna operations.
Dr. Chien holds B.S., M.S., and Ph.D. in Computer Science, all from the University of Illinois. Dr. Chien is also an Adjunct Assistant Professor with the Department of Computer Science of the University of Southern California. He is a 1995 recipient of the Lew Allen Award for Excellence, the highest honor JPL awards to researchers in the early years of their professional careers.
Dr. Brian Drabble is a member of Artificial Intelligence Applications Institute at the University of Edinburgh and has been actively involved in AI planning and scheduling research over the past 10 years. His current responsibilities include being project leader and co-principal investigator on the O-Plan projects which is part of the $66 million ARPA/Rome Laboratory Planning Initiative. In addition he has worked with a number of clients including Toshiba, Hitachi, European Space Agency, British Government, etc. to bringing AI planning and scheduling into their organizations and products. Dr. Drabble has supervised a number of Ph.D. and M.Sc students from the University's Department of Artificial Intelligence. The topics have included Reactive Execution Agents Models for Plan Based Diagnosis, and Knowledge Aquisition for Planning. He has also presented AIAI's Planning and Scheduling course to a large number of representatives from industry and commerce.