We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....
Recommender systems are intelligent E-commerce applications that assist users in a decision-making process by offering personalized product recommendations during an interaction s...
With standard assumptions the routing and wavelength assignment problem (RWA) can be viewed as a Markov Decision Process (MDP). The problem, however, defies an exact solution bec...
High-level vision systems use object, scene or domain specific knowledge to interpret images. Unfortunately, this knowledge has to be acquired for every domain. This makes it diffi...
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Abstract— This paper introduces a novel architecture for performing the core computations required by dynamic programming (DP) techniques. The latter pertain to a vast range of a...
—This paper studies the admission control and resource allocation in a cell-based wireless system that supports singlemedia and multirate services. Utilizing the idea of adaptive...
We consider a networked control system, where each subsystem evolves as a Markov decision process (MDP). Each subsystem is coupled to its neighbors via communication links over wh...