Waveform Coordination and Signal Processing across Multiple Degrees of Freedom for Radar

Abstract

The expected outcomes of this research include a detailed understanding of how the ACC facilitates rapid task adaptation and the development of AI algorithms capable of quick integration of new task features, thereby enhancing the adaptability of robotic agents. The practical application of these algorithms in both virtual and real-world scenarios holds significant potential for improving autonomous systems, with particular implications for military and defense applications. This research will significantly advance our understanding of brain plasticity mechanisms and inspire innovative AI approaches. By bridging the gap between neuroscience and artificial intelligence, the project aims to catalyze the development of autonomous systems with enhanced learning and adaptability, transforming their performance in dynamic environments. The long-term benefits of this research extend beyond immediate military applications, potentially influencing various sectors by providing more intelligent, flexible, and efficient autonomous systems.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2025
Source ID
FA95502410326

Entities

People

  • Ali Pezeshki

Organizations

  • Air Force Office of Scientific Research
  • Colorado State University
  • United States Air Force

Tags

Readers

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

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control