Phd Position On Cooperation Through Reputation in

4 maanden geleden

Amsterdam, Nederland Universiteit van Amsterdam Voltijd

PhD Position on Cooperation through Reputation in Multi-agent Reinforcement Learning

**Faculteit/Dienst**:Faculteit der Natuurw., Wiskunde & Informatica**Opleidingsniveau**:Master**Functie type**:Promotieplaats**Sluitingsdatum**:2 oktober 2024**Vacaturenummer**:13345
- Have you always wanted to design artificial agents that learn how to cooperate with each other? Are you passionate about developing AI systems where prosociality prevails? Do you enjoy working in an international and interdisciplinary research setting, at the interface of computer science, artificial intelligence, evolutionary biology, and game theory? If so, we have the right position for you We are looking for an ambitious doctoral student to join the project “Reputation as a new route to cooperation in multi-agent reinforcement learning”, at the Informatics Institute of the University of Amsterdam.- Altruistic cooperation requires that individuals incur a cost to provide a benefit to others. This has raised questions in many disciplines, from evolutionary biology to economics: Why did altruistic cooperation evolved through natural selection? How to explain and incentivise human cooperation in economic games? In Artificial Intelligence (AI), particularly in the sub-field of multi-agent systems, altruistic cooperation also poses unresolved questions: How to design a system where artificial agents autonomously learn to cooperate? Answering this question is fundamental to design socially intelligent AI and agents that can cooperate with others and humans. With this project we will explore the opportunities and challenges of considering reputation systems as a tool for cooperation in complex multi-agent reinforcement learning environments.- This project will resort to mathematical and computational tools such as reinforcement learning, agent-based simulations, (evolutionary) game theory and stochastic processes analysis.-
**What are you going to do?**- Conduct independent research in the area(s) of multi-agent systems simulation, multi-agent reinforcement learning and game theory;
- Develop new (optimized) computational models and systematically evaluate them locally and in high performance computing clusters;
- Read scientific literature and creatively suggest new research directions grounded in recent articles, in connection with cooperation, indirect reciprocity, reputation systems and multi-agent reinforcement learning;
- Present research results at international conferences and workshops and, in collaboration with the supervisors, write research articles to be published in academic journals and book chapters;
- Be an active member of our research community, participate in regular meetings and collaborate with other researchers at the Informatics Institute;
- Assist in teaching activities and/or supervising students;
- Complete and defend a PhD thesis within the official appointment duration of four years.

**What do you have to offer?**
- An MSc degree in Computer Science, Artificial Intelligence, Applied Mathematics/Physics, Complex Systems or related fields;
- A strong background/knowledge in computational modelling and reinforcement learning. Experience with evolutionary game theory and network science is a plus.
- Excellent programming skills preferably in Python, C++, or related languages. Experience with PyTorch is a plus.
- Strong communication, presentation and writing skills and an excellent command of English;
- Highly motivated, diligent, independent, and creative;
- Socially engaged, eager to work in a multidisciplinary environment.

**Our offer**
- A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is (until) March 2024, to be discussed during the interview(s). This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.-
- Besides the salary and a vibrant and challenging environment at Science Park, we offer you multiple fringe benefits:
- 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
- Multiple courses to follow from our Teaching and Learning Centre;
- A complete educational program for PhD students;
- Multiple courses on topics such as leadership for academic staff;
- Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
- 7 weeks birth leave (partner leave) with 100% salary;
- Partly paid parental leave;
- The possibility to set up a workplace at home;
- A pension at ABP for which UvA pays two third part of the contribution;
- The possibility to follow courses to learn Dutch;
- Help with housing for a studio or small apartment when you’re

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