Constructing Planners through Problem-Solving Methods

Constructing a planner for a particular application is a diicult job, for which little concrete support is currently available. The literature on planning is overwhelming and there is no clear synthesis of the various planning methods which could be used by knowledge engineers. In this paper, we show how a general, knowledge-level framework for conceptually specifying knowledge-based systems, can be of concrete use to support knowledge acquisition for planning systems. The framework encompasses three interrelated components: (1) problem-solving methods, (2) their assumptions and (3) domain knowledge. The presented analysis of planning performed in the framework can be considered as a library with reusable components, based on which planners can be conngured. Two experiments are presented that illustrate the use of the library in knowledge engineering.

[1]  Earl D. Sacerdott.  Planning in a hierarchy of abstraction spaces , 1973, IJCAI 1973.

[2]  Allen Newell,et al.  GPS, a program that simulates human thought , 1995 .

[3]  V. R. Benjamins,et al.  Problem-Solving Methods for Diagnosis and their Role in Knowledge Acquisition , 1996 .

[4]  Mark Drummond,et al.  Goal Ordering in Partially Ordered Plans , 1989, IJCAI.

[5]  Yolanda Gil,et al.  EXPECT: Explicit Representations for Flexible Acquisition , 1995 .

[6]  Manuela M. Veloso,et al.  The Need for Different Domain-independent Heuristics , 1994, AIPS.

[7]  V. Richard Benjamins,et al.  Modeling Planning Tasks , 1996, AIPS.

[8]  Nigel Shadbolt,et al.  Using Generalised Directive Models in Knowledge Acquisition , 1992, EKAW.

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

[10]  V. Richard Benjamins,et al.  On a Role of Problem Solving Methods in Knowledge Acquisition , 1994, EKAW.

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

[12]  Subbarao Kambhampati,et al.  Planning as Refinement Search: A Unified Framework for Evaluating Design Tradeoffs in Partial-Order Planning , 1995, Artif. Intell..

[13]  Christine Golbreich,et al.  Assumptions of Problem-Solving Methods , 1996, EKAW.

[14]  James A. Hendler,et al.  UMCP: A Sound and Complete Procedure for Hierarchical Task-network Planning , 1994, AIPS.

[15]  John McDermott,et al.  Usable and reusable programming constructs , 1991 .

[16]  Bob J. Wielinga,et al.  CommonKADS: a comprehensive methodology for KBS development , 1994, IEEE Expert.

[17]  Nigel Shadbolt,et al.  Domain and System Influences in Problem Solving Models for Planning , 1996, EKAW.

[18]  Oren Etzioni,et al.  PRODIGY4.0: The Manual and Tutorial , 1992 .

[19]  Subbarao Kambhampati,et al.  Refinement Search as a Unifying Framework for Analyzing Planning Algorithms , 1994, KR.

[20]  John Kingston,et al.  CommonKADS Models for Knowledge-Based Planning , 1996, AAAI/IAAI, Vol. 1.

[21]  B. Chandrasekaran,et al.  Design Problem Solving: A Task Analysis , 1990, AI Mag..

[22]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.

[23]  James A. Hendler,et al.  A Review of AI Planning Techniques , 1990 .

[24]  Craig A. Knoblock.  Building a Planner for Information Gathering: A Report from the Trenches , 1996, AIPS.

[25]  B. Chandrasekaran.  Generic TasksinKnowledge- BasedReasoning: High-Level Building Blocks forExpert SystemDesign , 1986 .

[26]  Klas Orsvärn.  Principles for Libraries of Task Decomposition Methods - Conclusions from a Case-study , 1996, EKAW.

[27]  Anthony Barrett,et al.  Partial-Order Planning: Evaluating Possible Efficiency Gains , 1994, Artificial Intelligence.

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

[29]  Dieter Fensel,et al.  Assumptions of Problem-Solving Methods and their Role in Knowledge Engineering , 1996, ECAI.

[30]  John McCarthy,et al.  SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .

[31]  Gerald Jay Sussman,et al.  A Computer Model of Skill Acquisition , 1975 .

[32]  Austin Tate,et al.  Advanced Planning Technology: Technological Achievements of the ARPA/Rome Laboratory Planning Inititive , 1996 .