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Found 3 papers, 0 papers with code
Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games
The core idea of our new algorithm is to create a new imitator to imitate the victim agent's policy while the adversarial policy will be trained not only based on interactions with the victim agent but also based on feedback from the imitator to forecast victim's intention.
The Art of Manipulation: Threat of Multi-Step Manipulative Attacks in Security Games
This paper studies the problem of multi-step manipulative attacks in Stackelberg security games, in which a clever attacker attempts to orchestrate its attacks over multiple time steps to mislead the defender's learning of the attacker's behavior.
Algorithmic Information Design in Multi-Player Games: Possibility and Limits in Singleton Congestion
This paper initiates the algorithmic information design of both \emph{public} and \emph{private} signaling in a fundamental class of games with negative externalities, i. e., singleton congestion games, with wide application in today's digital economy, machine scheduling, routing, etc.
