PhD student position in Neuro-Symbolic Synthesis and Reinforcement Learning
In this project we study a new approach to synthesis of efficient communication schemes in multi-agent systems, trained via reinforcement learning. We combine symbolic methods with machine learning, in what is referred to as a neuro-symbolic system, where a neural network learns to produce programs in a symbolic language to solve a task at hand. We believe this combination of neural and symbolic methods will be an important next step in the development of AI beyond todays capabilities.
This project is a collaboration between researchers at the division of Data Science and AIhttps://www.chalmers.se/en/departments/cse/research/dsai/Pages/default.aspx at Chalmers and the Center for Linguistic Theory and Studies in Probability (CLASP) at Gothenburg University.
Deadline for applications: 28 February: https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/