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Title: Stochastic approximation methods-Powerful tools for simulation and optimization: A survey of some recent work on multi-agent systems and cyber-physical systems

Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided.
Authors:
 [1] ;  [2] ;  [3]
  1. Department of Mathematics, Wayne State University, Detroit, MI 48202 (United States)
  2. Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202 (United States)
  3. Department Computer Science, Wayne State University, Detroit, MI 48202 (United States)
Publication Date:
OSTI Identifier:
22390770
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1637; Journal Issue: 1; Conference: ICNPAA 2014: 10. International Conference on Mathematical Problems in Engineering, Aerospace and Sciences, Narvik (Norway), 15-18 Jul 2014; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; APPROXIMATIONS; CONTROL; NETWORK ANALYSIS; OPTIMIZATION; PROCESSING; RANDOMNESS; STOCHASTIC PROCESSES; TOPOLOGY