With a few exceptions, current applications of deep RL have been limited to tasks that can be accurately simulated, like board and video games. One reason for this limitation is that current deep RL methods are data-inefficient, requiring large amounts of interaction data to learn, which can be expensive and time-consuming to gather in the real world. I am looking for students who would be interested in working with me to develop methods that would improve the data efficiency of deep RL agents and thereby facilitate the successful application of RL to a wider range of real-world tasks.

If you are interested in working with me, please refer to the 'Prospective Students' page on my website for more information and instructions on how to apply.

Accepting: PhD students

Express your interest in working with Dr. Janarthanan Rajendran .

When contacting us about your interest in a particular professor or fellowship, please include your:

• Research interests
• Past research experience
• Recent CV

Dalhousie's Faculty of Computer Science offers competitive funding to qualified graduate students and is committed to promoting excellence in research and teaching.