How can we design decentralized multiagent reinforcement learning (MARL) algorithms with equilibrium selection control? This is the central research question of this PhD project. We will be particularly interested in determining whether decentralized MARL algorithms used for pricing or trading can learn to collaborate to raise prices. By developing an understanding of if and how this is possible, we can inform policymakers on how to regulate the use of algorithms in such environments.
To address this issue, we will begin by characterizing the probability of reaching different equilibria under the dynamics of provably convergent decentralized MARL algorithms. With this characterization in hand, we will study how design choices in the algorithmic structure affect these probabilities. These two steps will initially be executed for simple environments and with deterministic dynamics, and then they will be scaled up to more complex environments with stochastic dynamics. Our starting point will be the Decentralized Q-learning algorithm, as it offers significant flexibility in its design and is provably convergent in a large class of games.Your profile
Are you interested in this position? Please send your application via the 'Apply now' button below before the 4th of March and include:
For more information regarding this position, you are welcome to contact (Janusz Meylahn at [email protected])About the department
The position will be in the Applied Mathematics department. The Applied Mathematics department has an active research portfolio in stochastic operations research, algorithmic discrete mathematics, complex networks, statistics, systems theory, computational science, and artificial intelligence with applications in health care, energy systems, traffic, and imaging. See MOR and SACS, and MDS
Our research group, Stochastic Operations Research (SOR), conducts mathematical education and research of internationally high standards in the areas of stochastic processes and mathematics of operations research to contribute to the development of mathematics in a multidisciplinary engineering environment and contribute to a better understanding and functioning of our increasingly complex society. See SOR.About the organisation
The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use nowadays, we embrace our role as contributors to a broad range of societal activities and as pioneers of tomorrow's digital society. As part of a people-first tech university that aims to shape society, individuals and connections, our faculty works together intensively with industrial partners and researchers in the Netherlands and abroad, and conducts extensive research for external commissioning parties and funders. Our research has a high profile both in the Netherlands and internationally. It has been accommodated in three multidisciplinary UT research institutes: Mesa+ Institute, TechMed Centre and Digital Society Institute.Want to know more? Meylahn, J. M. (Janusz)
Do you have questions about this vacancy? Then you can contact Janusz for all substantive questions about this position and the application procedure. For general questions about working for the UT, please refer to the chatbot.Contact
Email:[email protected]How to apply Step 1
Apply. When you see a vacancy that appeals to you, you can apply online. We ask you to upload a CV and motivation letter and/or list of publications. You will receive a confirmation of receipt by e-mail.Step 2
Selection. The selection committee will review your application and you will receive a response within 2 weeks after the vacancy has been closed.Step 3
1st interview. The 1st (online or in person) meeting serves as an introduction where we introduce ourselves to you and you to us. You may be asked to give a short presentation. This will be further explained in the invitation.Step 4
2nd interview. In the second interview, we will further discuss the job content, your skills and your talents.Step 5
The offer. If the conversations are positive, you will be made a suitable offer.Your Colleagues
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