Human Predictive Reasoning for Group Interactions

Abstract

In this effort, two approaches to predicting attitude and behavior of human groups are developed. One approach employs a novel statistical model for assessing group-level and individual-level factors on group constructs of interest. The second approach is more probabilistic in nature, and involves the use of a Markov chain with Bayesian updates in order to capture changes in group constructs as a function of changes in important environmental variables. These models were developed as alternative approaches to capturing the dynamics between group constructs of interest and important predictors of these group constructs. It is demonstrated how each model developed in this effort could be instantiated into the National Operational Environment Model (NOEM).

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2010
Accession Number
ADA535335

Entities

People

  • Jeremy D. Jordan
  • Marcus B. Perry
  • Patrick J. Vincent

Organizations

  • University of Alabama

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Climate Change
  • Computational Science
  • Data Science
  • Group Dynamics
  • Information Science
  • Markov Chains
  • Prejudice
  • Probability
  • Probability Distributions
  • Psychological Phenomena And Processes
  • Psychology
  • Reasoning
  • Social Psychology
  • Statistical Algorithms
  • Statistical Analysis

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Organizational Psychology.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference