A partially-observable markov decision process for dealing with dynamically changing environments - Chatzis, Sotirios P.; Kosmopoulos, Dimitrios I. (My University, 2014)
This paper offers a solution to the non-stationary POMDP problem, by making use of methods and concepts from the field of Bayesian non-parametrics, specifically dynamic hierarchical Dirichlet process priors. We combine block Gibbs sampling and importance sampling to perform inference. We evaluate the method in several benchmark policy learning tasks
Keywords: POMDP problem; Bayesian non-parametrics; Dirichlet process