My research focuses on merging computational and economic perspectives. As economic decisions are more and more mediated through software, we need to understand the economic consequences of interacting computations. This is particularly important, if we want to design new institutions.
I have been working on compositional game theory which provides a new mathematical foundation for game theory blending game theory and computations. On the basis of that theory, we have developed a software engine which allows to represent and analyze games (see here for more information and here for a tutorial how to use it). There are various applications of this framework, including the design of smart contracts as well protocol designs for blockchains. We have received a grant by the Ethereum foundation supporting the development of the software.
More recently, I have also started applying the framework to strategic decision-making of learning agents. One immediate application is the autonomous price-setting by companies using reinforcement learning. A question that naturally arise in such settings is whether autonomous pricing systems may lead to collusive behavior; whether dominant companies can leverage such system to further their dominance etc.
Lastly, I have worked on decision processes of individual agents in online settings. Such environments are intentionally designed and provide information as well as support functionality (filtering, sorting) for agents. The question is how agents are influenced by such environments and how they may even be able to leverage them for effective decision-making.