AbstractThe computational study of game-theoretic solution concepts is fundamental to describe the optimal behavior of rational agents interacting in a strategic setting, and to predict the most likely outcome of a game. Equilibrium computation techniques have been applied to numerous real-world problems. Among other applications, they are the key building block of the best poker-playing AI agents [5, 6, 27], and have been applied to physical and cybersecurity problems (see, e.g., [18, 20, 21, 30–32])
This dissertation combines three contributions to the literature on bounded rationality in games. Th...
We provide, to the best of our knowledge, the first computational study of extensive-form adversaria...
Most algorithmic studies on multi-agent information design so far have focused on the restricted sit...
AbstractA system with multiple interacting agents (whether artificial or human) is often best analyz...
It is challenging to reach a balance between desired cooperation among agents as the team tasks requ...
AbstractOver the last years,algorithmic game theoryhas received growing interest in AI, as it allows...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
In this paper we summarize concepts from earlier work and demonstrate how infinite sequential games ...
In many real-world settings agents engage in strategic interactions with multiple opposing agents wh...
This dissertation combines three contributions to the literature on bounded rationality in games. Th...
The first chapter studies global games with interim information acquisition, where players acquire a...
I study how to model various strategic interactions with incomplete information and how to properly ...
This dissertation combines three contributions to the literature on bounded rationality in games. Th...
We provide, to the best of our knowledge, the first computational study of extensive-form adversaria...
Most algorithmic studies on multi-agent information design so far have focused on the restricted sit...
AbstractA system with multiple interacting agents (whether artificial or human) is often best analyz...
It is challenging to reach a balance between desired cooperation among agents as the team tasks requ...
AbstractOver the last years,algorithmic game theoryhas received growing interest in AI, as it allows...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
It is challenging to reach a balance between desired cooperationamong agents as the team tasks requi...
In this paper we summarize concepts from earlier work and demonstrate how infinite sequential games ...
In many real-world settings agents engage in strategic interactions with multiple opposing agents wh...
This dissertation combines three contributions to the literature on bounded rationality in games. Th...
The first chapter studies global games with interim information acquisition, where players acquire a...
I study how to model various strategic interactions with incomplete information and how to properly ...
This dissertation combines three contributions to the literature on bounded rationality in games. Th...
We provide, to the best of our knowledge, the first computational study of extensive-form adversaria...
Most algorithmic studies on multi-agent information design so far have focused on the restricted sit...