Data-Driven and Expectation-Driven Discovery of Empirical Laws.

Abstract

BACON.5 is a program that discovers empirical laws for summarizing data. The system incorporates four data-driven heuristics for relating numeric terms, recursing to higher levels of description, postulating intrinsic properties such as mass and specific heat, and finding common divisors. BACON.5 also includes expectation-driven strategies for directing search based on discoveries that the program has already made. These include heuristics for expecting similar forms of laws, reducing the amount of data that must be gathered, and taking advantage of the symmetrical form of some laws. BACON.5 has shown its generality by rediscovering a number of laws from the history of physics and chemistry, including Snell's law of refraction, conservation of momentum, and Black's specific heat law.

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Document Details

Document Type
Technical Report
Publication Date
Oct 10, 1982
Accession Number
ADA120950

Entities

People

  • Gary L. Bradshaw
  • Herbert Simon
  • Patrick W. Langley

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Chemical Reactions
  • Chemistry
  • Data Reduction
  • Elements
  • Equations
  • Gas Laws
  • Ideal Gas Law
  • Kinetic Theory
  • Magnetic Resonance
  • Mass Spectroscopy
  • Nuclear Magnetic Resonance
  • Number Theory
  • Numbers
  • Organic Compounds
  • Polynomials
  • Security
  • Specific Heat

Readers

  • Fluid Dynamics.
  • Theoretical Analysis.
  • Wave Propagation and Nonlinear Chaotic Dynamics.