期刊名称：Journal of Automation, Mobile Robotics & Intelligent Systems (JAMRIS)
印刷版ISSN：1897-8649
电子版ISSN：2080-2145
出版年度：2006
卷号：27
页码：153-201
出版社：Industrial Research Inst. for Automation and Measurements, Warsaw
摘要：Efficient representations and solutions for large decision problems with
continuous and discrete variables are among the most important challenges faced
by the designers of automated decision support systems. In this paper, we
describe a novel hybrid factored Markov decision process (MDP) model that allows
for a compact representation of these problems, and a new hybrid approximate
linear programming (HALP) framework that permits their efficient solutions. The
central idea of HALP is to approximate the optimal value function by a linear
combination of basis functions and optimize its weights by linear programming.
We analyze both theoretical and computational aspects of this approach, and
demonstrate its scale-up potential on several hybrid optimization problems.
