Assessing and Improving Team Decision Making

Abstract

This project used analytical and experimental techniques derived from signal detection theory to quantify the decision making performance of individuals and teams. The basic decision task was to decide on the presence or absence of signals in noise. The project's experiments studied how individual and team performance depends on member signal-to-noise ratio, correlation among member inputs, efficiency of member updating of likelihood estimates, and constraints on member interaction and communication. The results show that: (a) members combine individual estimates with high efficiency to form the team's decision, relative to an optimal Bayesian rule, (b) team performance depends on the response protocol that constrains the sequential order of information exchange among team members, and (c) team members choose to acquire additional sources of information (varying in signal-to noise ratio, bias, cost, time, and correlation) in a near optimal manner.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 15, 2006
Accession Number
ADA443822

Entities

People

  • Ira Fishchler
  • Robert D. Sorkin

Organizations

  • University of Florida

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Acquisition
  • Air Force
  • Air Force Research Laboratories
  • Cognitive Science
  • Detection
  • Human Factors Engineering
  • Information Exchange
  • Information Theory
  • Observation
  • Organizational Structure
  • Psychology
  • Signal Detection
  • Social Psychology
  • Standards
  • Universities

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference