2023 American Control Conference (ACC) 2023
DOI: 10.23919/acc55779.2023.10156432
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Game Theory for Autonomy: From Min-Max Optimization to Equilibrium and Bounded Rationality Learning

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Cited by 5 publications
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“…We tuned the weights through the Human-inthe-loop experiments to imitate naturalistic behaviors. The competitive two-player game can be formulated as a zero-sum game [26]. We thus formulate the ego robot's reward as the negative reward (i.e., cost) of the opponent:…”
Section: A Reward Functionmentioning
confidence: 99%
“…We tuned the weights through the Human-inthe-loop experiments to imitate naturalistic behaviors. The competitive two-player game can be formulated as a zero-sum game [26]. We thus formulate the ego robot's reward as the negative reward (i.e., cost) of the opponent:…”
Section: A Reward Functionmentioning
confidence: 99%