Modeling, Control and Optimization of Complex Systems

In Honor of Professor Yu-Chi Ho
2003
ISBN: 978-1-4613-5411-6
Verlag: Springer US

Buch, Englisch, Band 14, 304 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 493 g

Reihe: The International Series on Discrete Event Dynamic Systems

Modeling, Control And Optimization Of Complex Systems is a collection of contributions from leading international researchers in the fields of dynamic systems, control theory, and modeling. These papers were presented at the Symposium on Modeling and Optimization of Complex Systems in honor of Larry Yu-Chi Ho in June 2001. They include exciting research topics such as:

-modeling of complex systems,
-power control in ad hoc wireless networks,
-adaptive control using multiple models,
-constrained control,
-linear quadratic control,
-discrete events,
-Markov decision processes and reinforcement learning,
-optimal control for discrete event and hybrid systems,
-optimal representation and visualization of multivariate data and functions in low-dimensional spaces.

Zielgruppe

Research

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung

Inhaltsverzeichnis

1 Optimal Representation and Visualization of Multivariate Data and Functions in Low-Dimensional Spaces.- 2 Modeling of Complex Systems.- 3 Power Control in ad hoc Wireless Networks: An Architectural Solution for a Melee of Multiple Agents, Cost Criteria), and Information Pattern.- 4 Some Examples of Optimal Control.- 5 Adaptive Control Using Multiple Models: A Methodology.- 6 Constrained Control: Poly topic Techniques.- 7 An Introduction to Constrained Control.- 8 On Feasibility of Interplanetary Travel: The Flight from Earth to Mars and Back.- 9 Linear Quadratic Control Revisited.- 10 Discrete Events: Timetables, Capacity Questions, and Planning Issues for Railway Systems.- 11 A Sensitivity View of Markov Decision Processes and Reinforcement Learning.- 12 Optimal Control for Discrete Event and Hybrid Systems.