Problems in Building an Instructable Production System.

Abstract

The Instructable Production System project is exploring the incremental growth properties of production systems (PSs) by constructing a generally intelligent problem solving system by gradual (external) instruction. The present task domain is an abstract job shop, in which finished goods are made from raw materials. We start with a Kernel (a small PS of about 200 productions) which has the basic capabilities to grow by instruction: (1) process a restricted natural language; (2) form productions from its input; (3) impose PS control conventions on them; and (4) perform basic manipulations in its environment. (We take the basic computational and representational adequacy of PSs for AI programs as established.) This note presents some immediate difficulties that are expected. These derive from the instructional situation: (1) The instructor can observe the system in the environment and can communicate with it freely, but cannot examine its internal structure directly; (2) Interaction with system is in an external language, analogous to natural language; (3) The initiative for interaction is mixed; (4) Instruction may be on any topic--specific tasks, general properties of tasks, the language of communication, possible errors, how to plan and explore, etc; and (5) Knowledge and system structure gained through instruction accumulates over the life of the system. The current approach uses means-ends analysis as the basic philosophy of both problem-solving and instruction.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1977
Accession Number
ADA043472

Entities

People

  • A. Newell
  • C. Forgy
  • J. Mcdermott
  • M. Rychener
  • P. Langley

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Computer Science
  • Computers
  • Environment
  • Formal Languages
  • Instructions
  • Instructors
  • Intelligent Systems
  • Language
  • Monitoring
  • Natural Languages
  • New York
  • Philosophy
  • Production
  • Scientific Research

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Linguistics