In this paper ε-MDP-models are introduced and convergence theorems are proven using the generalized MDP framework of Szepesvári and Littman. Using this model family, we show that Q-learning is capable of finding near-optimal policies in varying environments. The potential of this new family of MDP models is illustrated via a reinforcement learning algorithm called event-learning which separates...

Active set methods based on the augmented Lagrangian smoothing of nondiier-entiable optimization problems that arise in image restoration are discussed. One-dimensional image restoration problem and two diierent formulations for two-dimensional image restoration problem are given. Both nonmonotone and monotone active set algorithms are described and nite step convergence of the algorithms is co...

We investigate the complexity and approximability of the budget-constrained minimum cost flow problem, which is an extension of the traditional minimum cost flow problem by a second kind of costs associated with each edge, whose total value in a feasible flow is constrained by a given budget B. This problem can, e.g., be seen as the application of the ε-constraint method to the bicriteria minim...

Abstract The main goal of this article is to discuss a numerical method for finding the best constant in a Sobolev type inequality considered by C. Sundberg, and originating from Operator Theory. To simplify the investigation, we reduce the original problem to a parameterized family of simpler problems, which are constrained optimization problems from Calculus of Variations. To decouple the var...

We propose an augmented Lagrangian algorithm for solving large-scale equality constrained optimization problems. The novel feature of the algorithm is an adaptive update for the penalty parameter motivated by recently proposed techniques for exact penalty methods. This adaptive updating scheme greatly improves the overall performance of the algorithm without sacrificing the strengths of the cor...

To obtain efficient data gathering methods for wireless sensor networks (WSNs), a novel graph based transform regularized (GBTR) matrix completion algorithm is proposed. The graph based transform sparsity of the sensed data is explored, which is also considered as a penalty term in the matrix completion problem. The proposed GBTR-ADMM algorithm utilizes the alternating direction method of multi...

This analysis investigates the distortion of flow measurement and the increase of cavitation along orifice flowmeter. The analysis using the numerical method (CFD) validated the distortion of flow measurement through the inlet velocity profile considering the convergence and grid dependency. Realizable k-e model was selected and y+ was about 50 in this numerical analysis. This analysis also est...

This paper presents a multi-periodic, multi-echelon blood supply chain network consisting of blood donors, mobile collection units, local blood centers, main blood centers and demand points in which the local and main blood centers are subject to random failure in dispatching blood products to demand points. The problem has two objectives including minimization of the total chain costs and maxi...

During the epidemic outbreak period, number of infected people increased explosively. In order to effectively contain further spread and treat people, it is necessary make reasonable planning for treatment distribution materials. this paper, a multi-objective mixed-integer programming model integrated design emergency medical material networks developed, in which location points, allocation mat...

a f(x) dx (which one would use for instance to compute the work required to move a particle from a to b). For simplicity we shall restrict attention here to functions f : R → R which are continuous on the entire real line (and similarly, when we come to differential forms, we shall only discuss forms which are continuous on the entire domain). We shall also informally use terminology such as “i...