The Oz of Wizard: Simulating the Human for Interaction Research

Abstract

The Wizard of Oz experiment method has a long tradition of acceptance and use within the field of human-robot interaction. The community has traditionally downplayed the importance of interaction evaluations run with the inverse model: the human simulated to evaluate robot behavior, or "Oz of Wizard". We argue that such studies play an important role in the field of human-robot interaction. We differentiate between methodologically rigorous human modeling and placeholder simulations using simplified human models. Guidelines are proposed for when Oz of Wizard results should be considered acceptable. This paper also describes a framework for describing the various permutations of Wizard and Oz states.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA527048

Entities

People

  • Aaron Steinfeld
  • Brian Scassellati
  • Odest C. Jenkins

Organizations

  • Brown University

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognitive Systems Engineering
  • Communities
  • Computational Science
  • Computer Science
  • Human Behavior
  • Human-Computer Interaction
  • Human-Machine Interaction
  • Human-Robot Interaction
  • Machine Learning
  • Measurement
  • Psychology
  • Robotics
  • Robots
  • Simulations
  • Supervised Machine Learning
  • Test And Evaluation

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy
  • Autonomy - Human-Robot Interaction