Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Cacciamani, Federico"'
We study hidden-action principal-agent problems with multiple agents. Unlike previous work, we consider a general setting in which each agent has an arbitrary number of actions, and the joint action induces outcomes according to an arbitrary distribu
Externí odkaz:
http://arxiv.org/abs/2402.13824
We investigate the mechanism design problem faced by a principal who hires \emph{multiple} agents to gather and report costly information. Then, the principal exploits the information to make an informed decision. We model this problem as a game, whe
Externí odkaz:
http://arxiv.org/abs/2307.06210
Autor:
Zhang, Brian Hu, Farina, Gabriele, Anagnostides, Ioannis, Cacciamani, Federico, McAleer, Stephen Marcus, Haupt, Andreas Alexander, Celli, Andrea, Gatti, Nicola, Conitzer, Vincent, Sandholm, Tuomas
A mediator observes no-regret learners playing an extensive-form game repeatedly across $T$ rounds. The mediator attempts to steer players toward some desirable predetermined equilibrium by giving (nonnegative) payments to players. We call this the s
Externí odkaz:
http://arxiv.org/abs/2306.05221
Autor:
Zhang, Brian Hu, Farina, Gabriele, Anagnostides, Ioannis, Cacciamani, Federico, McAleer, Stephen Marcus, Haupt, Andreas Alexander, Celli, Andrea, Gatti, Nicola, Conitzer, Vincent, Sandholm, Tuomas
We introduce a new approach for computing optimal equilibria via learning in games. It applies to extensive-form settings with any number of players, including mechanism design, information design, and solution concepts such as correlated, communicat
Externí odkaz:
http://arxiv.org/abs/2306.05216
We study the problem of designing mechanisms for \emph{information acquisition} scenarios. This setting models strategic interactions between an uniformed \emph{receiver} and a set of informed \emph{senders}. In our model the senders receive informat
Externí odkaz:
http://arxiv.org/abs/2302.02873
\emph{Ex ante} correlation is becoming the mainstream approach for \emph{sequential adversarial team games}, where a team of players faces another team in a zero-sum game. It is known that team members' asymmetric information makes both equilibrium c
Externí odkaz:
http://arxiv.org/abs/2206.09161
The peculiarity of adversarial team games resides in the asymmetric information available to the team members during the play, which makes the equilibrium computation problem hard even with zero-sum payoffs. The algorithms available in the literature
Externí odkaz:
http://arxiv.org/abs/2201.10377
Many real-world scenarios involve teams of agents that have to coordinate their actions to reach a shared goal. We focus on the setting in which a team of agents faces an opponent in a zero-sum, imperfect-information game. Team members can coordinate
Externí odkaz:
http://arxiv.org/abs/2102.05026
Autor:
Bernasconi, Martino1 (AUTHOR), Cacciamani, Federico1 (AUTHOR), Castiglioni, Matteo1 (AUTHOR) matteo.castiglioni@polimi.it
Publikováno v:
Intelligenza Artificiale. 2023, Vol. 17 Issue 2, p195-205. 11p.
Autor:
Zhang, Brian Hu, Farina, Gabriele, Anagnostides, Ioannis, Cacciamani, Federico, McAleer, Stephen Marcus, Haupt, Andreas Alexander, Celli, Andrea, Gatti, Nicola, Conitzer, Vincent, Sandholm, Tuomas
We consider the problem of steering no-regret-learning agents to play desirable equilibria in extensive-form games via nonnegative payments. We show that steering is impossible if the total budget (across iterations) is finite. However, with average,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4eb09c5b30398a5339f83d6cfb7fdd4
http://arxiv.org/abs/2306.05221
http://arxiv.org/abs/2306.05221