Reinforcement Learning in MDPs with Information-Ordered Policies

Many operational Markov decision processes provide structured information where a trajectory generated under one policy may also reveal how other policies would have performed. We formalize this through an information order over a parameterized policy class, writing $π_{θ'} \preceq π_θ$ when data co