Accession Number:

AD1104463

Title:

Monte Carlo Tree Search Applied to a Modified Pursuit/Evasion Scotland Yard Game with Rendezvous Spaceflight Operation Applications

Descriptive Note:

Technical Report,01 Sep 2018,01 Jun 2020

Corporate Author:

AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH WRIGHT-PATTERSON AFB United States

Personal Author(s):

Report Date:

2020-06-01

Pagination or Media Count:

78.0

Abstract:

Space has become a warfighting domain. To combat threats, an understanding of tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence models use simulations to develop proper defensive and offensive TTPs capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based reinforcement learning model known for using limited domain knowledge to push favorable results.

Subject Categories:

  • Statistics and Probability
  • Unmanned Spacecraft
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE