HIERARCHICAL DESCRIPTIONS, UNIVERSAL SPACES AND ADAPTIVE SYSTEMS.

Abstract

The power of an adaptive system depends critically upon its ability to exploit common factors in successful techniques. Each time a device is tried, information accrues about components of each of the potential decompositions. Thus, the richer the variety of decompositions, the higher the effective sampling rate. Of course, to exploit this information about components, the adaptive system must use it to infer the performance of untried devices. And these inferences must, in turn, be used to plan which devices should be generated and tried next. At each stage, the flexibility and success of the process depends upon the flexibility and richness of the system's analysis and synthesis procedures. Among the many important procedures are those of: Substitution, Abstraction, Refinement, Modeling, Change of Representation, and Metacontrol. A structural formalism well-attuned to such procedures will exhibit three critical characteristics: Hierarchical Description, Self-Applicability, and Incorporation of Models. Formalisms with these characteristics are studied using a broad class of automaton representations, the class of compositions, which includes countably infinite devices such as von Neumann's cellular space and iterative circuit computers. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1968
Accession Number
AD0676211

Entities

People

  • John H. Holland

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Adaptive Systems
  • Automata
  • Computers
  • Decomposition
  • Resilience
  • Sampling

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.
  • Systems Analysis and Design

Technology Areas

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