Constructing Game Agents from Video of Human Behavior

Abstract

Developing computer game agents is often a lengthy and expensive undertaking. Detailed domain knowledge and decision-making procedures must be encoded into the agent to achieve realistic behavior. In this paper, we simplify this process by using the ICARUS cognitive architecture to construct game agents. The system acquires structured, high fidelity methods for agents that utilize a vocabulary of concepts familiar to game experts. We demonstrate our approach by first acquiring behaviors for football agents from video footage of college football games, and then applying the agents in a football simulator.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA554950

Entities

People

  • Dan Shapiro
  • David Aha
  • David J. Stracuzzi
  • Gary Cleveland
  • Kamal Ali
  • Matthew Molineaux
  • Nan Li
  • Tolga Konik

Organizations

  • Knexus Research (United States)

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Autonomous Agents
  • Cognitive Science
  • Computer Vision
  • Computers
  • Human Behavior
  • Intelligent Agents
  • Language
  • Machine Learning
  • Reinforcement Learning
  • Reliability
  • Simulators
  • Universities
  • Video
  • Video Games
  • Vocabulary

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Game Theory.