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Monte Carlo Tree Search Based Tactical Maneuvering

Artificial Intelligence 2020-09-21 v1 Machine Learning Multiagent Systems Robotics

Abstract

In this paper we explore the application of simultaneous move Monte Carlo Tree Search (MCTS) based online framework for tactical maneuvering between two unmanned aircrafts. Compared to other techniques, MCTS enables efficient search over long horizons and uses self-play to select best maneuver in the current state while accounting for the opponent aircraft tactics. We explore different algorithmic choices in MCTS and demonstrate the framework numerically in a simulated 2D tactical maneuvering application.

Keywords

Cite

@article{arxiv.2009.08807,
  title  = {Monte Carlo Tree Search Based Tactical Maneuvering},
  author = {Kunal Srivastava and Amit Surana},
  journal= {arXiv preprint arXiv:2009.08807},
  year   = {2020}
}
R2 v1 2026-06-23T18:38:22.128Z