Nikola Milosevic

Achievable visitation measures in reinforcement learning form a dually flat statistical manifold, transforming our understanding of planning-as-inference.

Active Inference can be framed as a convex MDP, revealing a surprising connection to performative reinforcement learning with robust policy improvement guarantees.