Richard Tsai: “Learning optimal strategies for line-of-sight based games“
High Dimensional Hamilton-Jacobi PDEs 2020
Workshop I: High Dimensional Hamilton-Jacobi Methods in Control and Differential Games
“Learning optimal strategies for line-of-sight based games“
Richard Tsai, University of Texas at Austin
Abstract: We present a few non-cooperative games that involve the line-of-sight of the players. The games are set in non-simply connected domains, i.e., domains that have obstacles blocking the lines-of-sights. We present Monte-Carlo-Tree Search (MCTS) based algorithms for op
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Richard Tsai: “Learning optimal strategies for line-of-sight based games“