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Modeling, Control and Optimization of Complex Systems: In Honor of Professor Yu-Chi Ho: The International Series on Discrete Event Dynamic Systems, cartea 14

Editat de Weibo Gong, Leyuan Shi
en Limba Engleză Paperback – 24 oct 2012
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.
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Specificații

ISBN-13: 9781461354116
ISBN-10: 1461354110
Pagini: 324
Ilustrații: XV, 304 p.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.45 kg
Ediția:2003
Editura: Springer Us
Colecția Springer
Seria The International Series on Discrete Event Dynamic Systems

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

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.