… For an MDP with known dynamics and finite state and action spaces, planning algorithms,
such … , “Bayesian control of large MDPs with unknown dynamics in data-poor environments,” in …

… Imani, SF Ghoreishi, and UM Braga-Neto, “Bayesian control of large MDPs with unknown
dynamics in data-poor environments,” in Advances in neural information processing systems, …

… with the parameter uncertainty in MDPs, we propose a new formulation, Bayesian risk MDP
(BR-… Bayesian control of large mdps with unknown dynamics in data-poor environments. In S. …

… Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments. In
Advances in Neural Information Processing Systems (NeurIPS), 8157–8167. …

… the critical infrastructure and the environment safe. This is, in … with each other in an uncertain
environment. The design of … , “Optimal control of gene regulatory networks with unknown …

… random and subject to some unknown probability distributions that reside in ambiguity sets.
… large number of interactions with the environment, model-based learning is known for high …

… We have developed Bayesian decision making framework for control of MDPs with … in this
section, we are concerned with large MDP with unknown dynamics in data-poor environments. …

… This paper proposes a Bayesian intervention policy that adaptively responds to cell
dynamic … The proposed Bayesian intervention policy takes action according to the posterior …

… control. At the same time, RL can also be applied to an unknown environment to find the
optimal control … to simulate the dynamic response under high-precision control requirements, …

… hmMDP for a large set of models so that we have a greater likelihood of including the real
model. However, in data-poor … while interacting with their environment while using some prior …