Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
We consider the problem of stock repurchase over a finite time horizon. We assume that a firm has a reservation price for the stock, which is the highest price that the firm is ...
Abstract. With many organizations now employing multiple data centres around the world to share global traffic load, it is important to understand the effects of geographical distr...
During service engagements, project managers frequently encounter resource constraint issues. For each resource shortfall encountered, a project manager must decide among a narrow...
We propose a method of approximate dynamic programming for Markov decision processes (MDPs) using algebraic decision diagrams (ADDs). We produce near-optimal value functions and p...