The book is about multidisciplinary science education. The challenges of our time, such as improving the length and quality of lives on Earth and short- and long-distance communication and transportation. In this book, we provide readers with the multidisciplinary education necessary to meet the scientific and technological challenges of our time while optimizing the college experience for students. The fundamental notions addressed in this book include gravitational forces and energy; dark matter and dark energy; heat transfer in solid Earth, stars’ interiors, and human bodies; electromagnetic radiation and spectroscopy; quantum entanglement and computing; accretion disks; matter in plasma state; and exoplanets. We illustrate the importance of these notions with applications across disciplines, including monitoring the deformation of the solid Earth’s surface using satellite measurements, unusual gravity anomalies in Antarctica, a view and characterization of the far side of our Moon, Earth’s climate, Titan’s anti-greenhouse effect, long-distance communication between Earth and the planets and exoplanets, etc. Finally, the book contains analytical and computational problems, including MATLAB software developed especially for the classes associated with this book. Key Features: • Contains multiple analytic and computational (MATLAB) exercises • Explores applications related to space programs' discoveries • Provides an accessible introduction and response to growing Multidisciplinary Science programs Dr. Luc Thomas Ikelle is a scientist with Imode Energy. He is also currently an adjunct professor in the Department of Geology and Geophysics at Texas A&M University. Previously, he worked at Cray Research Inc. in Minneapolis, developing 3D seismic inversion algorithms for CRAY Y-PM. From 1988 to 1997, he worked as a scientist for Schlumberger Geco-Prakla, Schlumberger Doll Research, and Schlumberger Cambridge Research. From 1997 to 2014, Dr. Ikelle was Robert R. Berg Professor in the Department of Geology and Geophysics at Texas A&M University. He earned a Ph.D. in geophysics and geochemistry from Paris 7 University in France. He received Le Prix de Thesis du CNRS in 1986 for his Ph.D. thesis, an SEG award in 2010 for his contribution to the creation of Geoscientists Without Borders, and a Texas AM University award as an outstanding scientist in 2012. He is a cofounder of Geoscientists Without Borders and of Imode Energy Research, and a member of SEG, AGU, and APS. Dr. Ikelle has worked as a DOE (US Department of Energy) special employer from 2005 to 2012 and was a member of Ultra-Deepwater Advisory Committee (an advisory committee to the Secretary of Energy) from 2005 to 2012.

Game theory is the mathematical study of interaction among independent, self-interested agents. The audience for game theory has grown dramatically in recent years, and now spans disciplines as diverse as political science, biology, psychology, economics, linguistics, sociology, and computer science, among others. What has been missing is a relatively short introduction to the field covering the common basis that anyone with a professional interest in game theory is likely to require. Such a text would minimize notation, ruthlessly focus on essentials, and yet not sacrifice rigor. This Synthesis Lecture aims to fill this gap by providing a concise and accessible introduction to the field. It covers the main classes of games, their representations, and the main concepts used to analyze them.

In the chapters in Part I of this textbook the author introduces the fundamental ideas of artificial intelligence and computational intelligence. In Part II he explains key AI methods such as search, evolutionary computing, logic-based reasoning, knowledge representation, rule-based systems, pattern recognition, neural networks, and cognitive architectures. Finally, in Part III, he expands the context to discuss theories of intelligence in philosophy and psychology, key applications of AI systems, and the likely future of artificial intelligence. A key feature of the author's approach is historical and biographical footnotes, stressing the multidisciplinary character of the field and its pioneers. The book is appropriate for advanced undergraduate and graduate courses in computer science, engineering, and other applied sciences, and the appendices offer short formal, mathematical models and notes to support the reader.

Communication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence. Likewise, recent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way. This timely and original textbook provides educators and students with a much-needed resource, connecting the dots between the science of AI and the discipline of communication studies. Clearly outlining the topic's scope, content and future, the text introduces key issues and debates, highlighting the importance and relevance of AI to communication studies. In lively and accessible prose, David Gunkel provides a new generation with the information, knowledge, and skills necessary to working and living in a world where social interaction is no longer restricted to humans. The first work of its kind, An Introduction to Communication and Artificial Intelligence is the go-to textbook for students and scholars getting to grips with this crucial interdisciplinary topic.

Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. - Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything - Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists - Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future - Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare

"By investigating the general structures of natural language and logic as well as relevant software engineering methodologies, the lectures presented in this book attempt the development of principled techniques for domain-independent IE. The book is based on the Second International School on Information Extraction, SCIE-99, held in Frascati near Rome, Italy in June/July 1999."--BOOK JACKET.

This volume thoroughly describes the fundamentals of a new multidisciplinary field of study that aims to deepen our understanding of the human body by combining medical image processing, mathematical analysis, and artificial intelligence. Multidisciplinary Computational Anatomy (MCA) offers an advanced diagnosis and therapeutic navigation system to help detect or predict human health problems from the micro-level to macro-level using a four-dimensional, dynamic approach to human anatomy: space, time, function, and pathology. Applying this dynamic and “living” approach in the clinical setting will promote better planning for – and more accurate, effective, and safe implementation of – medical management. Multidisciplinary Computational Anatomy will appeal not only to clinicians but also to a wide readership in various scientific fields such as basic science, engineering, image processing, and biomedical engineering. All chapters were written by respected specialists and feature abundant color illustrations. Moreover, the findings presented here share new insights into unresolved issues in the diagnosis and treatment of disease, and into the healthy human body.