Multi-party, Multi-issue, Multi-strategy Negotiation for Multi-modal Virtual Agents

Abstract

We present a model of negotiation for virtual agents that extends previous work to be more human-like and applicable to a broader range of situations, including more than two negotiators with different goals, and negotiating over multiple options. The agents can dynamically change their negotiating strategies based on the current values of several parameters and factors that can be updated in the course of the negotiation. We have implemented this model and done preliminary evaluation within a prototype training system and a three-party negotiation with two virtual humans and one human.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2008
Accession Number
AD1159210

Entities

People

  • Arno Hartholt
  • David R Traum
  • Jina Lee
  • Jonathan Gratch
  • Stacy C. Marsella

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy
  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Autonomous Agents
  • Computer Science
  • Demographic Cohorts
  • Engineering
  • Information Science
  • Language
  • Linguistics
  • Markup Languages
  • Military Research
  • Models
  • Natural Languages
  • Negotiations
  • Orientation (Direction)
  • Personality
  • Probability
  • Reasoning
  • Trainees
  • Training
  • Two Dimensional

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation