TOWARD AN UNDERSTANDING OF INFORMATION PROCESSES OF SCIENTIFIC INFERENCE IN THE CONTEXT OF ORGANIC CHEMISTRY,

Abstract

The program called Heuristic DENDRAL solves scientific induction problems of the following type: given the mass spectrum of an organic molecule, what is the most plausible hypothesis of organic structure that will serve to explain the given empirical data. Its problem solving power derives in large measure from the vast amount of chemical knowledge employed in controlling search and making evaluations. A brief description of the task environment and the program is given in Part 1. Recent improvements in the design of the program and the quality of its performance in the chemical task environment are noted. The acquisition of task-specific knowledge from chemist-'experts', the representation of this knowledge in a form best suited to facilitate the problem solving, and the most effective deployment of this body of knowledge in restricting search and making selections were major foci of the research. Part II discusses the techniques used and problems encountered in eliciting mass spectral theory from a cooperative chemist. A sample 'scenario' of a session of the representation of the chemical knowledge and the design of processes that utilize it effectively. The initial, rather straightforward, implementations were found to have serious defects. These are discussed. Part IV is concerned with our presently-conceived solutions to some of these problems, particularly the rigidity of processes and knowledge-structures. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1969
Accession Number
AD0708070

Entities

People

  • Bruce G. Buchanan
  • Edward A. Feigenbaum
  • Georgia L. Sutherland

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Artificial Intelligence
  • Chemistry
  • Deployment
  • Environment
  • Mass Spectra
  • Molecules
  • Organic Chemistry
  • Rigidity
  • Spectra
  • Test And Evaluation

Readers

  • Artificial Intelligence
  • Organic Chemistry
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms