Knowledge Representation and Reasoning for Mixed-Initiative Planning.

Abstract

This dissertation describes the formal foundations and implementation of a common sense, mixed-initiative plan reasoning system. By plan reasoning I mean the complete range of cognitive tasks that people perform with plans including, for example, plan construction (planning), plan recognition, plan evaluation and comparison, and plan repair (replanning), among other things. Mixed-initiative means that several participants can each make contributions to the plan under development through some form of communication. Common sense means that the system represents plans and their constituents at a level that is natural to us in the sense that they can be described and discussed in language. In addition, the reasoning that the system performs includes those conclusions that we would take to be sanctioned by common sense, including especially those conclusions that are defeasible given additional knowledge or time spent reasoning. The main theses of this dissertation are the following: Any representation of plans sufficient for common sense plan reasoning must be based on an expressive and natural representation of such underlying phenomena as time, properties, events, and actions. For mixed-initiative planning, plans should be viewed as arguments that a certain course of action under certain conditions will achieve certain goals. (AN)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1995
Accession Number
ADA293628

Entities

People

  • George M. Ferguson

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Networks
  • Causal Reasoning
  • Cognitive Science
  • Computational Linguistics
  • Computational Science
  • Computer Programming
  • Computer Science
  • Computers
  • Databases
  • Language
  • Linguistics
  • Natural Language Processing
  • Natural Languages
  • Ontologies
  • Psychology
  • Reasoning

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  • Artificial Intelligence