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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] References Here is the complete list of references mentioned on the slides. [Baker, 1974] K. Baker. Introduction to Sequencing and Scheduling. Wiley, 1974. [Baptiste & al, 1999] P. Baptiste, C. Le Pape and W. Nuijten. Satisfiability Tests and Time-Bound Adjustments for Cumulative Scheduling Problems. Annals of Operations Research, 92(1999)305-333. [Baptiste & al, 2001] P. 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