Scalability in planning with limited resources

Several temporal planning systems (e.g. Allen & Koomen, Descartes , parcPLAN) divide the planning process into two distinct phases: action introduction and plan verification. This thesis develops a detailed model of these two phases and their “interface”, and shows how the model can be exploited to enhance the efficiency of plan generation. The main focus is on plan verification, and the context is the temporal planner parcPLAN. Plan verification in parcPLAN is formally defined as a constraint satisfaction problem. The definition serves to clarify the structural dependencies of the problem and to identify limitations of existing methods. The approach in parcPLAN is extended in two key aspects. First, resource limitations are considered earlier in the search, and second, temporal and resource reasoning are integrated tightly through the use of probes. The resulting system, parcPLAN2, offers significant performance gains over parcPLAN. An extensive empirical study is undertaken to assess the performance of the overall planning approach in parcPLAN2. To gain perspective, parcPLAN2 is compared with two state-of-the-art planners, viz. IPP and Blackbox. On the benchmark experiments, parcPLAN2 outperforms IPP and Blackbox by a significant margin. The results show that the burden in plan verification can be managed effectively, but only up to a certain point. For certain types of problem parcPLAN2 scales well, but for others its effectiveness is limited.

[1]  Bernhard Nebel,et al.  Extending Planning Graphs to an ADL Subset , 1997, ECP.

[2]  Richard E. Korf,et al.  Depth-First Iterative-Deepening: An Optimal Admissible Tree Search , 1985, Artif. Intell..

[3]  James F. Allen,et al.  Planning Using a Temporal World Model , 1983, IJCAI.

[4]  Olivier Lhomme,et al.  Consistency Techniques for Numeric CSPs , 1993, IJCAI.

[5]  Amedeo Cesta,et al.  Recent Advances in AI Planning , 1997, Lecture Notes in Computer Science.

[6]  David Chapman,et al.  Planning for Conjunctive Goals , 1987, Artif. Intell..

[7]  Bart Selman,et al.  Planning as Satisfiability , 1992, ECAI.

[8]  Bart Selman,et al.  Pushing the Envelope: Planning, Propositional Logic and Stochastic Search , 1996, AAAI/IAAI, Vol. 2.

[9]  David A. McAllester,et al.  Systematic Nonlinear Planning , 1991, AAAI.

[10]  Tom Bylander,et al.  Complexity Results for Planning , 1991, IJCAI.

[11]  Hani El Sakkout Improving backtrack search : three case studies of localized dynamic hybridization , 1999 .

[12]  Malik Ghallab,et al.  Representation and Control in IxTeT, a Temporal Planner , 1994, AIPS.

[13]  Malik Ghallab,et al.  Planning with Sharable Resource Constraints , 1995, IJCAI.

[14]  M. Fox,et al.  Efficient Implementation of the Plan Graph in STAN , 2011, J. Artif. Intell. Res..

[15]  A. El-Kholy,et al.  Temporal and Resource Reasoning in Planning: the parcPLAN approach , 1996, ECAI.

[16]  Robert M. Haralick,et al.  Increasing Tree Search Efficiency for Constraint Satisfaction Problems , 1979, Artif. Intell..

[17]  Craig A. Knoblock,et al.  PDDL-the planning domain definition language , 1998 .

[18]  Austin Tate,et al.  The Use of Optimistic and Pessimistic Resource Profiles to Inform Search in an Activity Based Planner , 1994, AIPS.

[19]  Martha E. Pollack,et al.  Passive and active decision postponement in plan generation , 1996 .

[20]  Avrim Blum,et al.  Fast Planning Through Planning Graph Analysis , 1995, IJCAI.

[21]  James A. Hendler,et al.  Readings in Planning , 1994 .

[22]  Subbarao Kambhampati,et al.  Scaling up Planning by Teasing out Resource Scheduling , 1999, ECP.

[23]  Barry Richards,et al.  Least Commitment { An optimal planning strategyVassilis , 1997 .

[24]  Philippe Baptiste,et al.  A Theoretical and Experimental Comparison of Constraint Propagation Techniques for Disjunctive Scheduling , 1995, IJCAI.

[25]  James F. Allen Maintaining knowledge about temporal intervals , 1983, CACM.

[26]  Peter J. Stuckey,et al.  Programming with Constraints: An Introduction , 1998 .

[27]  John K. Slaney,et al.  Linear Time Near-Optimal Planning in the Blocks World , 1996, AAAI/IAAI, Vol. 2.

[28]  Henry A. Kautz,et al.  BLACKBOX: A New Approach to the Application of Theorem Proving to Problem Solving , 1998 .

[29]  Rina Dechter,et al.  Temporal Constraint Networks , 1989, Artif. Intell..

[30]  James A. Hendler,et al.  AI Planning: Systems and Techniques , 1990, AI Mag..

[31]  Martha E. Pollack,et al.  Is "Early Commitment" in Plan Generation Ever a Good Idea? , 1996, AAAI/IAAI, Vol. 2.

[32]  Dana S. Nau,et al.  On the Complexity of Blocks-World Planning , 1992, Artif. Intell..

[33]  Edward P. K. Tsang Plan Generation in a Temporal Frame , 1986, ECAI.

[34]  James F. Allen Planning as Temporal Reasoning , 1991, KR.

[35]  Bart Selman,et al.  Unifying SAT-based and Graph-based Planning , 1999, IJCAI.

[36]  Barry Richards,et al.  Scaleability in Planning , 1999, ECP.

[37]  Daniel S. Weld,et al.  UCPOP: A Sound, Complete, Partial Order Planner for ADL , 1992, KR.

[38]  Pascal Van Hentenryck,et al.  A Generic Arc-Consistency Algorithm and its Specializations , 1992, Artif. Intell..

[39]  Henry A. Kautz,et al.  Constraint propagation algorithms for temporal reasoning: a revised report , 1989 .

[40]  Barry Richards,et al.  parcPlan: A Planning Architecture with Parallel Actions, Resources and Constraints , 1994, ISMIS.