This position involves working on a project related to communication learning for joint cooperation in large multi-agent systems. The objective of this position includes contributing to the model development, solution, and implementation of novel communication learning methods using advanced reinforcement learning tools such as Graph Neural Networks. These models, once trained, will also be validated and tested in simulation on standard benchmarks (e.g., Starcraft Multi-Agent Challenge), as well as on actual robotic hardware on a number of cooperative multi-robot tasks (e.g., multi-agent pathfinding, search, or collaborative manipulation). The role involves the opportunity to work with the research team within the Mechanical Engineering department at the National University of Singapore. The successful candidate will be self-motivated with an outstanding track record in computer science, robotics, machine learning (in particular, reinforcement learning), or related disciplines. The main research tasks for the project include but will not be limited to:
Times Higher Education
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