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Effective solutions for real-world Stackelberg games: when agents must deal with human uncertainties.

, , , , , and . AAMAS (1), page 369-376. IFAAMAS, (2009)

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SAVES: a sustainable multiagent application to conserve building energy considering occupants., , , , , , , , , and . AAMAS, page 21-28. IFAAMAS, (2012)Signaling in Bayesian Stackelberg Games., , , , and . AAMAS, page 150-158. ACM, (2016)Towards Adjustable Autonomy for the Real World., , and . J. Artif. Intell. Res., (2002)Monitoring Teams by Overhearing: A Multi-Agent Plan-Recognition Approach., , and . J. Artif. Intell. Res., (2002)Monitoring Teams by Overhearing: A Multi-Agent Plan-Recognition Approach, , and . CoRR, (2011)A Dynamic Distributed Constraint Satisfaction Approach to Resource Allocation., , , , and . CP, volume 2239 of Lecture Notes in Computer Science, page 685-700. Springer, (2001)Automated Assistants to Aid Humans in Understanding Team Behaviors., , and . RoboCup, volume 1856 of Lecture Notes in Computer Science, page 85-102. Springer, (1999)Effective solutions for real-world Stackelberg games: when agents must deal with human uncertainties., , , , , and . AAMAS (1), page 369-376. IFAAMAS, (2009)Sensitivity analysis for distributed optimization with resource constraints., , , and . AAMAS (1), page 633-640. IFAAMAS, (2009)Decision-Focused Learning of Adversary Behavior in Security Games., , , , , and . CoRR, (2019)