Toward Undifferentiated Cognitive Agents: Translating Instructions to Knowledge

Abstract

Autonomous systems are a new frontier for pushing sociotechnical advancement. Such systems will eventually become pervasive, involved in everything from manufacturing, healthcare, defense, and even research itself. However, proliferation is stifled by the high development costs and the resulting inflexibility of the produced systems. The current time needed to create and integrate state of the art autonomous systems that operate as team members in complex situations is a 3-15 year development period, often requiring humans to adapt to limitations in the resulting systems. A new research thrust in interactive task learning (ITL; Laird, Gluck, et al., 2017) has begun, calling for natural human-autonomy interaction to facilitate system flexibility and minimize users’ complexity in providing autonomous systems with new tasks.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 11, 2018
Source ID
FA95501810371

Entities

People

  • Dario D Salvucci

Organizations

  • Air Force Office of Scientific Research
  • Drexel University
  • United States Air Force

Tags

Readers

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

Technology Areas

  • Autonomy
  • Autonomy - Human-Robot Interaction