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The development of basic planning technology has made important strides forward in recent years. Some new efficient approaches to AI planning have been proposed (Graphplan-based planning, SAT/CSP-based planning, planning as model checking, efficient HTN planning, planning as heuristic search, etc.) which have dramatically increased the scale and complexity of problem instances that can be tackled by domain-independent technology. The planning systems based on these approaches have been shown to be drastically more efficient than earlier ones, and therefore constitute a promising foundation for real application. Whilst many of these planning approaches have so far been focussed on highly restricted domain representations there have been some important recent developments in the expressive power of the domain representation languages that can be handled, allowing the modelling of time, continuous processes and resources. Much of the power of the modern planning approaches derives from their effective search algorithms and heuristics, the efficient representations of the search spaces they explore, and from the ability of some of these systems to exploit domain knowledge, either supplied by a domain expert or automatically inferred using domain analysis techniques.
The school will bring together subject experts, from several countries in Europe and America, in order to introduce the broad range of current planning approaches and to consider ways of developing and exploiting these to make planning a realistically usable tool for complex problem-solving.
The school is aimed at PhD students and young
academic researchers. In order to ensure the success of the school
it has been decided to restrict registrations to a maximum of 40.
Dr. Malik Ghallab
(LAAS-CNRS, France)
Planning
with time and resources
Prof. Subbarao
Kambhampati (Arizona State University, USA)
A
Unifying and Brand-Name-Free Introduction to Planning
Dr. Derek Long
(University
of Durham, UK)
Pre-processing
and Domain Analysis
Prof. Dana Nau
(University
of Maryland, USA)
Ordered
Task Decomposition: Theory and Applications
Prof. Bernhard
Nebel (University of Freiburg, Germany)
Computational
Complexity of Planning and Expressiveness of Planning Formalisms
Dr. Paolo
Traverso (IRST-ITC, Italy)
Planning
as model checking
IJCAI, Inc.