Discrete event modeling and simulation technologies

The computing world has witnessed during the 1990s many advances in areas such as mobile and enterprise computing. The common underlying basis enabling the realization of various facets of these dinds of computing is Modeling, Simulation, and Artificial Intelligence. With the enterprise computing in areas as diverse as manufacturing, health organization, and commerce, the need for a disciplined, multifaceted, unified approach to modeling and simulation has become essential. This new book provides a forum for scientists, academicians, and professionals alike from around the globe to present their latest and exciting research findings in various fields of artificial intelligence, collaborative/distributed computing, modeling, simulation, and their integration. Whereas some of these research areas continue to seek answers to basic fundamental scientific inquiries that have remained unanswered for more than half a century, other questions have emerged only recently due to advances in various areas of computing infrastructure, technologies, and techniques. The principal objective of this book is to provide a unifying forum for developing postmodern AI-based modeling & simulation environments and their utilization in traditional application domains as well as those deemed to be vital in future technologies. Readership: R&D professionals and practitioners in CS, software engineering, AI, and computer modeling.

Contents

• Simulation-based acquisition: toward a unified foundation
• Why engineering models do not have a frame problem
• Adaptive designs for multiresolution, multiperspective modeling
• The role of uncertainty in systems modeling
• Linguistic dynamic systems and computing with words for modeling, simulation and analysis of complex systems
• Toward a modeling formalism for conflict management
• Systems design: a simulation modeling framework
• DEVS framework for systems development: unified specification for logical analysis, performance evaluation and implementation
• Representation of dynamic structure discrete event models: a systems theory approach
• Timed cell-DEVS: modeling and simulation of cell spaces
• DEVS-based modeling and simulation for intelligent transportation systems
• Dynamic neuronal ensembles: neurobiologically inspired discrete event neural networks
• Simulation for meaning generation: multiscale coalitions of autonomous agents
• Evolutionary learning in agent-based modeling
• A system theoretic approach to constructing test beds for multiagent systems
• A methodology for the translation of knowledge between heterogeneous planners
• Toward a systems methodology for object-oriented software analysis