Experienced Researcher in Decentralized Multiagent Reinforcement Learning
3 weken geleden
Central Research Question
We are looking for a highly motivated and enthusiastic researcher to join our team and tackle the central research question of this PhD project: How can we design decentralized multiagent reinforcement learning (MARL) algorithms with equilibrium selection control?
To address this issue, the successful candidate will characterize the probability of reaching different equilibria under the dynamics of provably convergent decentralized MARL algorithms. They will then study how design choices in the algorithmic structure affect these probabilities. This involves scaling up the research to more complex environments with stochastic dynamics.
Your Profile
- You are a highly motivated researcher with a strong background in mathematics, theoretical computer science, or theoretical physics.
- The societal impact of your work plays a significant role in your motivation.
- You have a creative mindset, excellent analytical and communication skills, and a good team spirit.
- You are proficient in English and have a good understanding of reinforcement learning and/or game theory.
- The UT and the faculty EEMCS are inclusive toward underrepresented groups and strive to increase the proportion of female staff.
Our Offer
- You will be appointed to a full-time position for four years, with a qualifier in the first year, within a very stimulating and exciting scientific environment.
- The University offers a dynamic ecosystem with enthusiastic colleagues and a competitive salary and benefits package.
- As a PhD candidate, you will have the opportunity to work on a cutting-edge research project and contribute to the development of new algorithms and techniques.
- Our team is dedicated to providing a supportive and inclusive environment, and we encourage a high degree of responsibility and independence.
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Enschede, Overijssel, Nederland University of Twente VoltijdWe are seeking a highly motivated PhD researcher to join our team at the University of Twente in the field of decentralized multiagent reinforcement learning. As a researcher, you will be part of a dynamic and international environment where you will contribute to the development of novel MARL algorithms and their applications in real-world scenarios.**Key...
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