Improving Cognitive Models and Artificial Cognition
Abstract
Previously funded JCTD. This project is a joint U.S. - India JCTD that will create architectures and modules that monitor and predict fatigue, provide new interaction capabilities, and allow autonomous systems to learn through interactive tasks. The overall architecture, which will use a combination of adaptive control of thought—rational and logic architecture will be demonstrated on two separate tasks: finding people and finding objects. The goal is to build the basic level architecture to learn how to find people and objects by improving embodied cognition, human robot interaction, and interactive task learning. In FY 2017 computational cognitive models for embodied cognition, human-robot interaction, and interactive task learning were developed. Experiments were conducted on autonomous systems to find people and objects in different environments. Transition is targeted for the U.S. Marine Corps Warfighting Lab, U.S. Navy Explosive Ordinance Disposal Technology Division, U.S. Special Operations Command, U.S. Border Protection, and the India Defense Research Development Organization.
Document Details
- Document Type
- Accomplishment
- Publication Date
- Oct 01, 2019
- Source ID
- d41eaa7f9e052daa98e13efc8a5bf5bd