Issues in Human-Agent Communication

Abstract

The report covers issues pertinent to the design and evaluation of the communication between humans and intelligent software agents necessary to enable a collaborative relationship. For human-agent interaction to be robust in a dynamic real-world situation, both software agents and humans must be able to communicate their overall intent in terms of mission objectives. Because of differences in their reasoning processes, capabilities, and knowledge bases, humans and agents are not an analog for human teams. We discuss the technical issues involved in effective communication including models of mutual transparency, natural language processing (NLP), artificial intelligence (AI), and explainable AI. Lacking a theory of mind, which enables humans to gain insight into their teammates mental processes, agents have a difficult time anticipating human information needs and future actions. Research in collaborative planning involving multiple agents and research into synthetic shared mental models are used as exemplars of attempts to integrate humans and agents into a synergistic unit. However, we conclude that progress in NLP, explainable AI, and human science will be necessary before humans and agents communicate like human teams during complex, uncertain missions.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2019
Accession Number
AD1067050

Entities

People

  • Eric Holder
  • J. Y. Chen
  • Michael J. Barnes
  • Shan Lakhmani

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Automata Theory
  • Automation
  • Autonomous Systems
  • Cognition
  • Cognitive Workload
  • Computational Science
  • Computer Languages
  • Computer Science
  • Control Systems
  • Deep Learning
  • Engineering
  • Language
  • Linguistics
  • Machine Learning
  • Mental Processes
  • Military Research
  • Multiagent Systems
  • Natural Language Computing
  • Natural Language Processing
  • Natural Languages
  • Psychological Theory
  • Psychology
  • Reasoning
  • Transparencies
  • Unmanned Aerial Vehicles
  • Unmanned Systems
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

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

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy