The internship involves exploring how Reservoir Computing can be leveraged in the context of Meta-RL. The intern will consider evolving the architecture of a reservoir for performing well on a wide range of RL tasks. The project will involve designing a wide range of RL tasks in an existing simulation environment, learning how to learn multiple tasks without access to the goal information (i.e. meta-RL with a reservoir), and evolving reservoir architectures for meta-RL with evolutionary methods.