We are expecting funded GRA positions to be available (starting Spring 2020) for motivated M.S. students interested in robot learning and multi-agent systems!
You will be part of a team of graduate and undergraduate students, and a research scientist (yours truly) attempting to advance the state-of-the-art in robot learning and multi-agent systems. The project is titled “Learning Task Requirements from Demonstrations for Heterogeneous Multi-Agent Teams” and is expected start in Spring 2020. Within the context of a heterogeneous (i.e., diverse) team of agents attempting to solve a variety of tasks, this project aims to learn the various capabilities necessary to perform the tasks. In other words, we are interested in understanding how the various capabilities of the agents contribute to accomplishing each task and how to coordinate a diverse team of agents to successfully accomplish all the tasks. Specifically, assuming access to examples that reflect optimal assignments of agents to tasks, we would like to effectively and efficiently learn the factors that were implicitly considered in such assignments, and in turn, how to perform these assignments autonomously.
Ideal candidates for these positions will have a strong background in machine learning, robotics, and programming. In particular, we would like to encourage candidates who have the following skills to apply.
- Strong background in machine learning and robotics (e.g., imitation learning, reinforcement learning, sampling methods, and transfer learning.)
- Excellent written and verbal communication skills
- Strong programming skills in Python, C/C++, and ROS
How to apply?
If interested, please e-mail me (email@example.com) with the subject line “GRA candidate: Learning Task Requirements“. Please include the following in your email:
- Cover letter
- If available, links to prior work/experience (papers, code repositories, etc.)
If you have any questions or require any further information, please feel free to reach out via email.