COMPOSITIONALLY VERIFIABLE REINFORCEMENT LEARNING SYSTEMS AND DISTRIBUTED TESTING

Abstract

The objective of the proposed effort is to develop theory and algorithms toward establishing a framework for verifiable and compositional development of multi-agent systems that integrate reinforcement learning (RL) algorithms.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 20, 2023
Source ID
FA95502210403

Entities

People

  • Ufuk Topcu

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Texas at Austin

Tags

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML