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International Summer School on AI Planning 2002
September 16-22, 2002
Halkidiki, Greece
Planning with Resources
Philippe Laborie
Planning with Resources
Abstract
A resource can be defined as any substance or (set of) object(s) whose cost or available quantity induce
some constraint on the operations that use it. A resource can for instance represent a machine which can
only perform one operation at a time, the fuel contained in the tank of a plane or the workforce or the
money available to perform a given project. In the context of planning with resources, a solution plan is
defined as a plan that achieves the goals while allocating resources to operations in such a way that all
resource constraints are satisfied. As in the real life resources often have a limited availability, it's not
surprising that resource constraints play a key role in practical planning.
The first part of the course will provide a definition of resources in the context of planning and review the
state-of-the-art of planning with resources. The second part will focus on one of the most promising
approach for dealing with resources in planning which relies on the application of constraint-based
techniques in Partial-Order or Hierarchical Task Network planning.
Outline
Foreword:
● Why are Resources important in many practical applications of AI Planning
Part I: State of the Art Overview
● Definition of a Resource
● Problem Modeling
○ Limits of STRIPS model
○ Standalone languages
PDDL2.1
BTPL
○ Planning Systems (language)
parcPLAN
I XT ET
O-Plan
ASPEN
RAX-PS
● Problem Solving
○ Basic Tools
Linear Programming (LP)
Integer Linear Programming (ILP)
Satisfiability (SAT)
Constraint Satisfaction Problems (CSP)
○ Planning Techniques
Planning graphs: R-IPP
SAT Planners: LPSAT
Heuristic Planners: GRT-R, Metric-FF, Sapa, TP4
Part II: Focus on Constraint-Based Approaches
● Problem Solving (cont’d)
○ Planning Techniques
Partial-Order Causal-Link Planners
Hierarchical Task Networks
● Constraint Programming
● Problem Modeling
○ Activities
○ Temporal Constraints
○ Resource Usage
○ Objective Functions
● Problem Solving
○ Constraint Propagation
Global constraints
Algorithms based on activity time windows
Algorithms based on relative positions of activities
○ Search
Branching Schemes
Search heuristics
Beyond the Basic Search Scheme
Conclusion
Some Planning Systems on the Web
ASPEN
BlackBox/SatPlan
CPlan
EXCALIBUR
FF
GP-CSP
Graphplan
GRT
HSP
IPP
IXTET
LPG
LPSAT
Metric-FF
O-Plan
parcPLAN
RAX
Sapa
SHOP
Sipe
STAN
TP4
UCPOP
UMCP
http://www-aig.jpl.nasa.gov/public/planning/aspen/aspen_index.html
http://www.cs.washington.edu/homes/kautz/blackbox
http://ai.uwaterloo.ca/~vanbeek
http://www.ai-center.com/projects/excalibur
http://www.informatik.uni-freiburg.de/~hoffmann/ff.html
http://rakaposhi.eas.asu.edu/gp-csp.html
http://www-2.cs.cmu.edu/~avrim/graphplan.html
http://www.csd.auth.gr/~lpis/GRT/main.html
http://www.ldc.usb.ve/~hector
http://www.informatik.uni-freiburg.de/~koehler/ipp.html
http://www.laas.fr/RIA/IxTeT/ixtet-planner.html (in French)
http://prometeo.ing.unibs.it/lpg
http://www.cs.washington.edu/ai/lpsat.html
http://www.informatik.uni-freiburg.de/~hoffmann/metric-ff.html
http://www.aiai.ed.ac.uk/~oplan
http://www-icparc.doc.ic.ac.uk/parcPlan
http://ic.arc.nasa.gov/projects/remote-agent
http://rakaposhi.eas.asu.edu/sapa.html
http://www.cs.umd.edu/projects/shop
http://www.ai.sri.com/~sipe
http://www.dur.ac.uk/computer.science/research/stanstuff/stanpage.html
http://www.ida.liu.se/~pahas/hsps
http://www.cs.washington.edu/ai/ucpop.html
http://www.cs.umd.edu/projects/plus/umcp
About the lecturer
Dr. Philippe Laborie graduated from Ecole Nationale Supérieure des Télécommunications (Paris) in
1992, and received a Ph.D. in Artificial Intelligence from LAAS/CNRS (Toulouse) on the integration of
A.I. Planning and Scheduling in 1995. He is one of the developers of the I XTET Planning system. He then
worked for two years as post-doctoral fellow at Electricité de France (Paris) and INRIA/IRISA (Rennes)
on the Supervision and Diagnosis of complex systems (telecommunication and power distribution
networks). His main scientific interests include planning, scheduling, supervision and diagnosis of
complex systems and more generally, all decision problems dealing with time. Since 1998 he has been at
ILOG S.A. in Gentilly, France, where he currently holds the position of Principal Scientist.
E-mail: [email protected]
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