Simulation and synthesis are core parts of the future of AI and machine learning. Consider: programmers, data scientists, and machine learning engineers can create the brain of a self-driving car without the car. Rather than use information from the real world, you can synthesize artificial data using simulations to train traditional machine learning models.That’s just the beginning. With this practical book, you’ll explore the possibilities of simulation- and synthesis-based machine learning and AI, concentrating on deep reinforcement learning and imitation learning techniques. AI and ML are increasingly data driven, and simulations are a powerful, engaging way to unlock their full potential. You'll learn how to: Design an approach for solving ML and AI problems using simulations with the Unity engine Use a game engine to synthesize images for use as training data Create simulation environments designed for training deep reinforcement learning and imitation learning models Use and apply efficient general-purpose algorithms for simulation-based ML, such as proximal policy optimization Train a variety of ML models using different approaches Enable ML tools to work with industry-standard game development tools, using PyTorch, and the Unity ML-Agents and Perception Toolkits
Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model. This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence.
This book brings together contributions to the Fourth Artificial Life Workshop, held at the Massachusetts Institute of Technology in the summer of 1994.
As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.
This interdisciplinary approach to computer modeling addresses both traditional simulationists seeking the greater representational flexibility and ease of use that AI techniques offer, and computer scientists seeking the greater power and realism that rigorous simulation techniques can provide. First section reveals the theoretical underpinnings of AI and simulation. Second section describes application of simulation techniques to current problems in AI research. Third section discusses application of AI methods to simulation.
The Simulation Hypothesis, by best-selling author, renowned MIT computer scientist and Silicon Valley video game designer Rizwan Virk, is the first serious book to explain one of the most daring and consequential theories of our time. Riz is the Executive Director of Play Labs @ MIT, a video game startup incubator at the MIT Game Lab. Drawing from research and concepts from computer science, artificial intelligence, video games, quantum physics, and referencing both speculative fiction and ancient eastern spiritual texts, Virk shows how all of these traditions come together to point to the idea that we may be inside a simulated reality like the Matrix. The Simulation Hypothesis is the idea that our physical reality, far from being a solid physical universe, is part of an increasingly sophisticated video game-like simulation, where we all have multiple lives, consisting of pixels with its own internal clock run by some giant Artificial Intelligence. Simulation theory explains some of the biggest mysteries of quantum and relativistic physics, such as quantum indeterminacy, parallel universes, and the integral nature of the speed of light. Recently, the idea that we may be living in a giant video game has received a lot of attention: “There’s a one in a billion chance we are not living in a simulation” -Elon Musk “I find it hard to argue we are not in a simulation.” -Neil deGrasse Tyson “We are living in computer generated reality.” -Philip K. Dick Video game technology has developed from basic arcade and text adventures to MMORPGs. Video game designer Riz Virk shows how these games may continue to evolve in the future, including virtual reality, augmented reality, Artificial Intelligence, and quantum computing. This book shows how this evolution could lead us to the point of being able to develop all encompassing virtual worlds like the Oasis in Ready Player One, or the simulated reality in the Matrix. While the idea sounds like science fiction, many scientists, engineers, and professors have given the Simulation Hypothesis serious consideration. Futurist Ray Kurzweil has popularized the idea of downloading our consciousness into a silicon based device, which would mean we are just digital information after all. Some, like Oxford lecturer Nick Bostrom, goes further and thinks we may in fact be artificially intelligent consciousness inside such a simulation already! But the Simulation Hypothesis is not just a modern idea. Philosophers like Plato have been telling us that we live in a “cave” and can only see shadows of the real world. Mystics of all traditions have long contended that we are living in some kind of “illusion “and that there are other realities which we can access with our minds. While even Judeo-Christian traditions have this idea, Eastern traditions like Buddhism and Hinduism make this idea part of their core tradition — that we are inside a dream world (“Maya” or illusion, or Vishnu’s Dream), and we have “multiple lives” playing different characters when one dies, continuing to gain experience and “level up” after completing certain challenges. Sounds a lot like a video game! Whether you are a computer scientist, a fan of science fiction like the Matrix movies, a video game enthusiast, or a spiritual seeker, The Simulation Hypothesis touches on all these areas, and you will never look at the world the same way again!
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering
This book creates the emergence of disruptive technologies that have led to a significant change in the role of mathematics and statistics for problem solving, with the use of sophisticated software and hardware in solving complex systems and process. In the era of digital technology, mathematics and statistics need to be highly relevant to be able to cater for the needs of IR4.0 such as big data analytics, simulation, autonomous system, and cloud computing. Motivated by this development, a total of 26 chapters are contributed by respectable experts for this book. The main scope of the book is to conduct a new system of modeling and simulations on solving differential equations, nonlinear equations, energy, epidemiology, and risk assessment. This book is of interest for postgraduate students, researchers as well as other scientists who are working in numerical modeling and simulations based on efficient mathematical and statistical techniques.
