Integrating general purpose planners and specialized reasoners: case study of a hybrid planning architecture

Many real-world planning problems involve substantial amounts of domain-specific reasoning that is either awkward or inefficient to encode in a general purpose planner. A hybrid planning architecture for such domains is proposed. It utilizes a set of specialists to complement both the overall expressiveness and the efficiency of a traditional hierarchical planner. Such an architecture promises to retain the flexibility and generality of a classical planning framework while allowing deeper and more efficient domain-specific reasoning through specialists. The architecture has several ramifications on the internal operations of the planner as well as its interactions with the specialists. Continual interactions between the planner and the specialists necessitate an incremental, interactive, and least-commitment oriented approach to planning. As the planner and the specialists in such a model may use heterogeneous reasoning mechanisms and representations, a complete understanding of the operations of one by the other is not possible. >

[1]  Jean-Claude Latombe,et al.  Making Compromises Among Antagonist Constraints in a Planner , 1985, Artif. Intell..

[2]  James A. Hendler,et al.  A Validation-Structure-Based Theory of Plan Modification and Reuse , 1992, Artif. Intell..

[3]  Caroline C. Hayes Using Goal Interactions to Guide Planning , 1987, AAAI.

[4]  David E. Wilkins,et al.  Domain-Independent Planning: Representation and Plan Generation , 1984, Artif. Intell..

[5]  Lenhart K. Schubert,et al.  Using Specialists to Accelerate General Reasoning , 1988, AAAI.

[6]  Subbarao Kambhampati,et al.  Combining Specialized Reasoners and General Purpose Planners: A Case Study , 1991, AAAI.

[7]  Earl David Sacerdoti,et al.  A Structure for Plans and Behavior , 1977 .

[8]  Katia P. Sycara,et al.  Resolving Goal Conflicts via Negotiation , 1988, AAAI.

[9]  Jay M. Tenenbaum,et al.  Toward an Intelligent Agent Flamework for Enterprise Integration , 1991, AAAI.

[10]  S. Kambhampati Characterizing multi-contributor causal structures for planning , 1992 .

[11]  Mark R. Cutkosky,et al.  A methodology and computational framework for concurrent product and process design , 1990 .

[12]  Randall H. Wilson,et al.  Maintaining geometric dependencies in an assembly planner , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[13]  AMY L. LANSKY,et al.  Localized event‐based reasoning for multiagent domain 1 , 1988, Comput. Intell..

[14]  Victor R. Lesser,et al.  Knowledge-Based Conflict Resolution for Cooperation Among Expert Agents , 1991, MIT-JSME Workshop.

[15]  Hector J. Levesque,et al.  An Essential Hybrid Reasoning System: Knowledge and Symbol Level Accounts of KRYPTON , 1985, IJCAI.

[16]  Subbarao Kambhampati,et al.  A Theory of Plan Modification , 1990, AAAI.

[17]  Reid G. Simmons,et al.  Generate, Test and Debug: Combining Associational Rules and Causal Models , 1987, IJCAI.

[18]  Austin Tate,et al.  Generating Project Networks , 1977, IJCAI.

[19]  Mark Klein,et al.  Supporting conflict resolution in cooperative design systems , 1991, IEEE Trans. Syst. Man Cybern..

[20]  Edmund H. Durfee,et al.  Predictability Versus Responsiveness: Coordinating Problem Solvers in Dynamic Domains , 1988, AAAI.

[21]  Michael N. Huhns,et al.  Distributed Truth Maintenance , 1990, AAAI.

[22]  Subbarao Kambhampati,et al.  Incremental and interactive geometric reasoning for fixture and process planning , 1991 .

[23]  Subbarao Kambhampati,et al.  Approach toward incremental and interactive planning for concurrent product and process design , 1990 .

[24]  Mark R. Cutkosky,et al.  PACT: an experiment in integrating concurrent engineering systems , 1993, Computer.