Dynamics of Information Systems: Algorithmic Approaches

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Alexey Sorokin, Panos M. Pardalos
Springer Science & Business Media, Aug 23, 2013 - Business & Economics - 344 pages

Dynamics of Information Systems: Algorithmic Approaches presents recent developments and results found by participants of the Fourth International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 20-22, 2012. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems.Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: detection of terrorist networks, design of highly efficient businesses, computer networks, quantum entanglement, genome modeling, multi-robotic systems, and industrial and manufacturing safety.

The book contains state-of-the-art work on theory and practice relevant to the dynamics of information systems. It covers algorithmic approaches to numerical computations with infinite and infinitesimal numbers; presents important problems arising in service-oriented systems, such as dynamic composition and analysis of modern service-oriented information systems and estimation of customer service times on a rail network from GPS data; addresses the complexity of the problems arising in stochastic and distributed systems; and discusses modulating communication for improving multi-agent learning convergence. Network issues—in particular minimum-risk maximum-clique problems, vulnerability of sensor networks, influence diffusion, community detection, and link prediction in social network analysis, as well as a comparative analysis of algorithms for transmission network expansion planning—are described in later chapters.


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Theory and Applications
Dynamic Composition and Analysis of Modern ServiceOriented Information Systems
Estimating Customer Service Times on a Rail Networkfrom GPS Data
A RiskAverse GameTheoretic Approach to Distributed Control
Static Teams and Stochastic Games
Output Feedback and Performance Risk Aversion
Modulating Communication to Improve Multiagent Learning Convergence
MinimumRisk Maximum Clique Problem
Models for Assessing Vulnerability in Imperfect Sensor Networks
Minimum Connected Sensor Cover and MaximumLifetime Coverage in Wireless Sensor Networks
Influence Diffusion Community Detection and Link Prediction in Social Network Analysis
Comparative Analysis of Local Search Strategiesfor Transmission Network Expansion Planning

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