A Planning Model with Problem Analysis and Operator Hierarchy

Authors:
K.-H. Chang;W. G. Wee
Affiliations:
Auburn Univ., Auburn, AL;Univ. of Cincinnati, Cincinnati, OH
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1988

Citing 5
Cited 1

Domain-independent planning: representation and plan generation

Artificial Intelligence
A planning model with problem analysis and operator hierarchy

A planning model with problem analysis and operator hierarchy
Principles of artificial intelligence

Principles of artificial intelligence
Planning with constraints

Planning with constraints
Knowledge-based experiment design in molecular genetics

Knowledge-based experiment design in molecular genetics

An agent-oriented multiagent planning system

CSC '93 Proceedings of the 1993 ACM conference on Computer science

Quantified Score

Hi-index	0.14

Visualization

Abstract

A planning model described in terms of its goal analysis and hierarchical operator representation is presented. With this system, successful plans have been made for nonlinear problems that are described as a conjunction of subgoals. The system uses heuristic rules to analyze the problem, and thus achieves an ordered sequence of subgoals and constraints that can be achieved successively without interfering with each other. The operators are designed in a goal-oriented fashion and are stored in operator hierarchies. During the plan generation phase, each subgoal is mapped into a goal operator, which is further refined to meet details and specific conditions of the problem. As the generation phase follows the analysis, conflicts among subgoals are eliminated implicitly.