By Topic

Solving sequential decision-making problems under virtual reality simulation system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Yang Xianglong ; Syst. Simulation Lab., Beijing Univ. of Aeronaut. & Astronaut., China ; Feng Yuncheng ; Li Tao ; Wang Fei

A large class of problems of sequential decision-making can be modeled as Markov or semi-Markov decision problems, which can be solved by classical methods of dynamic programming. However, the computational complexity of classical MDP algorithms, such as value iteration and policy iteration, is prohibitive and will grow intractably with problem size. Furthermore, they require for each action the one step transition probability and reward matrices, which is often unrealistic for large and complex systems. We provide the decision-maker with a sequential decision-making environment by establishing a virtual reality simulation system, where the uncertainty property of the system can also be shown. In order to obtain the optimal or near optimal policy of the sequential decision problem, simulation optimization algorithms as infinitesimal perturbation analysis are applied to complex queuing systems. We present a detailed study of this method in the sequential decision-making problem in the Boeing-737 assembling process

Published in:

Simulation Conference, 2001. Proceedings of the Winter  (Volume:2 )

Date of Conference: