Optimizing Human Input in Social Network Analysis

Abstract

The study focused on developing new bandit algorithms for online optimization (e.g. matching tasks to human agents). The attached technical reports provide details on the formulations and results. Specifically, the technical reports focused on a backlog minimization formulation for matching tasks and agents, as well as a contextual bandit formulation focusing on dimensionality reduction.

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Document Details

Document Type
Technical Report
Publication Date
Jan 23, 2018
Accession Number
AD1051572

Entities

People

  • Sanjay Shakkottai

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Bernoulli Distribution
  • Compressed Sensing
  • Data Sets
  • Dimensionality Reduction
  • Equations
  • Generative Models
  • Information Processing
  • Machine Learning
  • Phase Transformations
  • Probability
  • Random Variables
  • Simulations
  • Social Sciences
  • Standards
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Operations Research
  • Technical Research and Report Writing.