Militarized Conflict Modeling Using Computational Intelligence

Computational modeling is now ubiquitous in psychology, and researchers who are not modelers may find it increasingly difficult to follow the theoretical developments in their field. This book presents an integrated framework for the development and application of models in psychology and related disciplines. Researchers and students are given the knowledge and tools to interpret models published in their area, as well as to develop, fit, and test their own models. Both the development of models and key features of any model are covered, as are the applications of models in a variety of domains across the behavioural sciences. A number of chapters are devoted to fitting models using maximum likelihood and Bayesian estimation, including fitting hierarchical and mixture models. Model comparison is described as a core philosophy of scientific inference, and the use of models to understand theories and advance scientific discourse is explained.

Medical Informatics (MI) is an emerging interdisciplinary science. This book deals with the application of computational intelligence in MI. Addressing the various issues of medical informatics using

This book highlights major issues related to big data analysis using computational intelligence techniques, mostly interdisciplinary in nature. It comprises chapters on computational intelligence tech

This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, ge

The advent of supercomputers has brought computational fluid dynamics (CFD) to the forefront as a tool to analyze increasingly complex simulation scenarios in many fields. Computational aerodynamics problems are also increasingly moving towards being coupled, multi-physics and multi-scale with complex, moving geometries. The latter presents severe geometry handling and meshing challenges. Simulations also frequently use formal design optimization processes. This book explains the evolution of CFD and provides a comprehensive overview of the plethora of tools and methods available for solving complex scenarios while exploring the future directions and possible outcomes. Using numerous examples, illustrations and computational methods the author discusses turbulence modeling, pre and post processing, coupled solutions, the importance of design optimization, multiphysics problems, reduced order models, and large scale computations and the future of CFD. Advanced Computational Fluid and Ae

This book constitutes the second part of the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2014, and of the International Conference on Intelligent

The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems.This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field.New for the second edition:“Programming-language agnostic” presentation using pseudocode.New chapter 1 covering

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques to the detection, mitigation, treatment, and elimination of the COVID-19 virus around the world. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes. Data Science for COVID-19, Volume 2 extends the coverage of Volume 1 into research on statistical data and applications of Data Science to a variety of perspectives for analysis and understanding of the wide variety of impacts COVID-19 is having on societies and medical practice around the world.

The exposure of two senior republicans as informers for British intelligence in 2005 led to a popular perception that the IRA had 'lost' the intelligence war and was pressurised into peace. In this first in-depth study across the entire conflict, Thomas Leahy re-evaluates the successes and failures of Britain's intelligence activities against the IRA, from the use of agents and informers to special-forces, surveillance and electronic intelligence. Using new interview material alongside memoirs and Irish and UK archival materials, he suggests that the IRA was not forced into peace by British intelligence. His work sheds new light on key questions in intelligence and security studies. How does British intelligence operate against paramilitaries? Is it effective? When should governments 'talk to terrorists'? And does regional variation explain the outcome of intelligence conflicts? This is a major contribution to the history of the conflict and of why peace emerged in Northern Ireland.

Intractability is a growing concern across the cognitive sciences: while many models of cognition can describe and predict human behavior in the lab, it remains unclear how these models can scale to situations of real-world complexity. Cognition and Intractability is the first book to provide an accessible introduction to computational complexity analysis and its application to questions of intractability in cognitive science. Covering both classical and parameterized complexity analysis, it introduces the mathematical concepts and proof techniques that can be used to test one's intuition of (in)tractability. It also describes how these tools can be applied to cognitive modeling to deal with intractability, and its ramifications, in a systematic way. Aimed at students and researchers in philosophy, cognitive neuroscience, psychology, artificial intelligence, and linguistics who want to build a firm understanding of intractability and its implications in their modeling work, it is an id

Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models

Hendrik Herold explores potentials and hindrances of using retrospective geoinformation for monitoring, communicating, modeling, and eventually understanding the complex and gradually evolving process

Interval Finite Element Method with MATLAB provides a thorough introduction to an effective way of investigating problems involving uncertainty using computational modeling. The well-known and versati

Contrary to popular mythology, the designs of favorable products and successful systems do not appear suddenly, or magically. This second edition of Engineering Design demonstrates that symbolic representation and related problem-solving methods, offer significant opportunities to clarify and articulate concepts of design to lay a better framework for design research and design education. Artificial Intelligence (AI) provides a substantial body of material concerned with understanding and modeling cognitive processes. This book adopts the vocabulary and a paradigm of AI to enhance the presentation and explanation of design. It includes concepts from AI because of their explanatory power and their utility as possible ingredients of practical design activity. This second edition has been enriched by the inclusion of recent work on design reasoning, computational design, AI in design, and design cognition, with pointers to a wide cross section of the current literature.

This book offers an approach for modeling and investigating economic and social systems using of agent-based simulations and other computational techniques, in order to analyze systems-level outcomes

Creativity is a topic that has traditionally interested psychologists, historians and biographers. Developments in cognitive science and artificial intelligence have provided a powerful computational framework in which creativity can be studied and the creative process can be described and explained. In this book, creativity in technology is discussed using such a computational approach. Using an important historical episode in computer technology as a case study, namely the invention of microprogramming by Maurice Wilkes in 1951, the author presents a plausible explanation of the process by which Wilkes may have arrived at his invention. Based on this case study, the author has also proposed some very general hypotheses concerning creativity that appear to corroborate the findings of some psychologists and historians and then suggests that creative thinking is not significantly different in nature from everyday thinking and reasoning.

Media argumentation is a powerful force in our lives. From political speeches to television commercials to war propaganda, it can effectively mobilize political action, influence the public, and market products. This book presents a new and systematic way of thinking about the influence of mass media in our lives, showing the intersection of media sources with argumentation theory, informal logic, computational theory, and theories of persuasion. Using a variety of case studies that represent arguments that typically occur in the mass media, Douglas Walton demonstrates how tools recently developed in argumentation theory can be usefully applied to the identification, analysis, and evaluation of media arguments. He draws upon the most recent developments in artificial intelligence, including dialogical theories of argument, which he developed, as well as speech act theory. Each chapter presents solutions to problems central to understanding, analyzing, and criticizing media argumentatio

In our day-to-day lives we constantly make decisions which are simply 'good enough' rather than optimal. Most computer-based decision-making algorithms, on the other hand, doggedly seek only the optimal solution based on rigid criteria and reject any others. In this book, Professor Stirling outlines an alternative approach, using novel algorithms and techniques which can be used to find satisficing solutions. Building on traditional decision and game theory, these techniques allow decision-making systems to cope with more subtle situations where self and group interests conflict, perfect solutions can't be found and human issues need to be taken into account - in short, more closely modelling the way humans make decisions. The book will therefore be of great interest to engineers, computer scientists and mathematicians working on artificial intelligence and expert systems.

This book explains how to build Natural Language Generation (NLG) systems - computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English or other human languages, either in isolation or as part of multimedia documents, Web pages, and speech output systems. Typically starting from some non-linguistic representation of information as input, NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It also discusses engineering issues such as system architecture, requirements analysis, and the integration of text generation into multimedia and speech output systems.

Partial differential equations arise in almost all areas of science, engineering, modeling, and forecasting. During the last two decades pseudospectral methods have emerged as successful alternatives to better known computational procedures, (e.g. finite difference and finite element methods of numerical solution), in several key application areas. These areas include computational fluid dynamics, wave motion, and weather forecasting. This book explains how, when and why this pseudospectral approach works. In order to make the subject accessible to students as well as researchers and engineers, the subject is presented using illustrations, examples, heuristic explanations, and algorithms rather than rigorous theoretical arguments. This book will be of interest to graduate students, scientists and engineers interested in applying pseudospectral methods to real problems.