Synopses & Reviews
The underlying technologies enabling the realization of recent advances in areas like mobile and enterprise computing are artificial intelligence (AI), modeling and simulation, and software engineering. A disciplined, multifaceted, and unified approach to modeling and simulation is now essential in new frontiers, such as Simulation Based Acquisition. This volume is an edited survey of international scientists, academicians, and professionals who present their latest research findings in the various fields of AI; collaborative/distributed computing; and modeling, simulation, and their integration. Whereas some of these areas continue to seek answers to basic fundamental scientific inquiries, new questions have emerged only recently due to advances in computing infrastructures, technologies, and tools. The book¿s principal goal is to provide a unifying forum for developing postmodern, AI-based modeling and simulation environments and their utilization in both traditional and modern application domains. Features and topics: * Blends comprehensive, advanced modeling and simulation theories and methodologies in a presentation founded on formal, system-theoretic and AI-based approaches * Uses detailed, real-world examples to illustrate key concepts in systems theory, modeling, simulation, object orientation, and intelligent systems * Addresses a broad range of critical topics in the areas of modeling frameworks, distributed and high-performance object-oriented simulation approaches, as well as robotics, learning, multi-scale and multi-resolution models, and multi-agent systems * Includes new results pertaining to intelligent and agent-based modeling, the relationship between AI-based reasoning and Discrete-Event System Specification, and large-scale distributed modeling and simulation frameworks * Provides cross-disciplinary insight into how computer science, computer engineering, and systems engineering can collectively provide a rich set of theories and methods enabling contemporary modeling and simulation This state-of-the-art survey on collaborative/distributed modeling and simulation computing environments is an essential resource for the latest developments and tools in the field for all computer scientists, systems engineers, and software engineers. Professionals, practitioners, and graduate students will find this reference invaluable to their work involving computer simulation, distributed modeling, discrete-event systems, AI, and software engineering.
Synopsis
The initial ideas behind this edited volume started in spring of 1998 - some two years before the sixtieth birthday of Bernard P. Zeigler. The idea was to bring together distinguished researchers, colleagues, and former students of Professor Zeigler to present their latest findings at the AIS' 2000 conference. During the spring of 1999, the initial ideas evolved into creating a volume of articles surrounding seminal concepts pertaining to modeling and simulation as proposed, developed, and advocated by Professor Zeigler throughout his scientific career. Also included would be articles describing progress covering related aspects of software engineering and artificial intelligence. As this volume is emphasizing concepts and ideas spawned by the work of Bernard P. Zeigler, it is most appropriate to offer a biographical sketch of his scientific life, thus putting into a historical perspective the contributions presented in this volume as well as new research directions that may lie ahead Bernard P. Zeigler was born March 5, 1940, in Montreal, Quebec, Canada, where he obtained his bachelor's degree in engineering physics in 1962 from McGill University. Two years later, having completed his MS degree in electrical engineering at the Massachusetts Institute of Technology, he spent a year at the National Research Council in Ottawa. Returning to academia, he became a Ph. D. student in computer and communication sciences at the University of Michigan, Ann Arbor.
Synopsis
This book is a state-of-the-art survey on collaborative/distributed modeling and simulation computing environments. Leading researchers provide up-to-date presentations on new methods and emerging technologies for intelligent, networked computing paradigms. The computing world has witnessed extraordinary advances in areas such as mobile and enterprise computing. With enterprise computing spanning areas as diverse as manufacturing, health organizations, and commerce, the need for a multifaceted, unified approach to modeling and simulation has become essential.
Synopsis
During the 1990s the computing industry has witnessed many advances in mobile and enterprise computing. Many of these advances have been made possible by developments in the areas such as modeling, simulation, and artificial intelligence. Within the different areas of enterprise computing - such as manufacturing, health organisation, and commerce - the need for a disciplined, multifaceted, and unified approach to modeling and simulation has become essential. This new book provides a forum for scientists, academics, and professionals to present their latest research findings from the various fields: artificial intelligence, collaborative/distributed computing, modeling, and simulation.
Table of 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.