ReLExS: Reinforcement Learning Explanations for Stackelberg No-Regret Learners

Xiangge Huang, Jingyuan Li, Jiaqing Xie
8/26/2024
cs.GTcs.LG

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Abstract

With the constraint of a no regret follower, will the players in a two-player Stackelberg game still reach Stackelberg equilibrium? We first show when the follower strategy is either reward-average or transform-reward-average, the two players can always get the Stackelberg Equilibrium. Then, we extend that the players can achieve the Stackelberg equilibrium in the two-player game under the no regret constraint. Also, we show a strict upper bound of the follower's utility difference between with and without no regret constraint. Moreover, in constant-sum two-player Stackelberg games with non-regret action sequences, we ensure the total optimal utility of the game remains also bounded.

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Cite this paper

@article{huang2024relexs,
  title  = {ReLExS: Reinforcement Learning Explanations for Stackelberg No-Regret Learners},
  author = {Xiangge Huang and Jingyuan Li and Jiaqing Xie},
  year   = {2024},
  eprint = {2408.14086},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.14086v1}
}

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