Anna Harutyunyan - Academia.edu (original) (raw)
Uploads
Papers by Anna Harutyunyan
The principal contribution of this paper is a conceptual framework for off-policy reinforcement l... more The principal contribution of this paper is a conceptual framework for off-policy reinforcement learning, based on conditional expectations of importance sampling ratios. This framework yields new perspectives and understanding of existing off-policy algorithms, and reveals a broad space of unexplored algorithms. We theoretically analyse this space, and concretely investigate several algorithms that arise from this framework.
The principal contribution of this paper is a conceptual framework for off-policy reinforcement l... more The principal contribution of this paper is a conceptual framework for off-policy reinforcement learning, based on conditional expectations of importance sampling ratios. This framework yields new perspectives and understanding of existing off-policy algorithms, and reveals a broad space of unexplored algorithms. We theoretically analyse this space, and concretely investigate several algorithms that arise from this framework.