MICROSTRUCTURE OF GUESS PROCESSES: PART C

Abstract

Trial-to-trial changes in the proportion of human subjects predicting the occurrence of one of two events in a complex sequence of binary events (probability learning) are analyzed in terms of several simple models. The direction of change predicted by linear-operator reinforcement models (Estes, Bush and Mosteller) is wrong on about 75% of the trials. A no-learning model, a time-dependent decay model, and a cycle-dependent decay model are used to provide some insight into the nature of probability learning. Some suboptimal procedures for estimating parameters of stochastic processes are compared. The method of minimum absolute error is recommended as being very useful.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1963
Accession Number
AD0600474

Entities

People

  • Masanao Toda

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Continents
  • Data Analysis
  • Deception
  • Engineering
  • Equations
  • Governments
  • Learning
  • Mathematical Models
  • Microstructure
  • Models
  • Numbers
  • Probability
  • Real Numbers
  • Sequences
  • Statistics
  • Systems Engineering

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation
  • Structural Health Monitoring of Composite Structures.