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Creating superior intelligence would be the biggest event in human history. Unfortunately, according to the world's pre-eminent AI expert, it could also be the last. In this ground-breaking book on the biggest question facing humanity, Stuart Russell explains why he has come to consider his own discipline an existential threat to his own species, and lays out how we can change course before it's too late. There is no one better placed to assess the promise and perils of the dominant technology of the future than Russell, who has spent decades at the forefront of AI research. Through brilliant analogies and crisp, lucid prose, he explains how AI actually works, how it has an enormous capacity to improve our lives - but why we must ensure that we never lose control of machines more powerful than we are. Here Russell shows how we can avert the worst threats by reshaping the foundations of AI to guarantee that machines pursue our objectives, not theirs. Profound, urgent and visionary, Human Compatible is the one book everyone needs to read to understand a future that is coming sooner than we think.
Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computer science --- artificial intelligence --- KI (kunstmatige intelligentie) --- Artificial intelligence --- Robotics --- Human-computer interaction --- #SBIB:309H1730 --- #SBIB:39A4 --- #SBIB:17H16 --- Computer-human interaction --- Human factors in computing systems --- Interaction, Human-computer --- Human engineering --- User-centered system design --- User interfaces (Computer systems) --- Automation --- Machine theory --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Artificiële Intelligentie, knowledge engineering, .. --- Toegepaste antropologie --- Cultuur en ethiek --- Mathematical linguistics --- Artificial intelligence. --- Moral and ethical aspects. --- Artificiële Intelligentie, knowledge engineering, . --- Artificiële Intelligentie, knowledge engineering,
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In this third edition, the authors have updated the treatment of all major areas. A new organizing principle -- the representational dimension of atomic, factored, and structured models -- has been added. Significant new material has been provided in areas such as partially observable search, contingency planning, hierarchical planning, relational and first-order probability models, regularization and loss functions in machine learning, kernel methods, Web search engines, information extraction, and learning in vision and robotics. The book also includes hundreds of new exercises.
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Artificial intelligence --- 006.3 --- artificiële intelligentie --- Artificiële intelligentie --- Artificiële intelligentie. --- 681.3*I2 --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- 681.3*I2 Artificial intelligence. AI --- Artificial intelligence. AI --- Artificial intelligence. --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Artificial intelligence. Robotics. Simulation. Graphics --- E-books
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In this third edition, the authors have updated the treatment of all major areas. A new organizing principle--the representational dimension of atomic, factored, and structured models--has been added. Significant new material has been provided in areas such as partially observable search, contingency planning, hierarchical planning, relational and first-order probability models, regularization and loss functions in machine learning, kernel methods, Web search engines, information extraction, and learning in vision and robotics. The book also includes hundreds of new exercises.
Artificial intelligence. Robotics. Simulation. Graphics --- Artificial intelligence --- 681.3*I2 --- 681.3*I2 Artificial intelligence. AI --- Artificial intelligence. AI --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers
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"Probabilistic programming is a programming paradigm in which code models are used to draw probabilistic inferences from data. By applying specialized algorithms, programs assign degrees of probability to conclusions and make it possible to forecast future events like sales trends, computer system failures, experimental outcomes, and other critical concerns. The book explains how to use the PP paradigm to model application domains and express those probabilistic models in code. It shows how to use the Figaro language to build a spam filter and apply Bayesian and Markov networks to diagnose computer system data problems and recover digital images. Then it dives into the world of probabilistic inference, where algorithms help turn the extended prediction of social media usage into a science. The book covers functional-style programming for text analysis and using object-oriented models to predict social phenomena like the spread of tweets, and using open universe models to model real-life social media usage. It also teaches the principles of algorithms such as belief propagation and Markov chain Monte Carlo. The book closes out with modeling dynamic systems by using a product cycle as its main example and explains how probabilistic models can help in the decision-making process for an ad campaign."--Provided by publisher.
Stochastic programming --- Probabilities --- Data processing
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Like Mooki, the hero of Spike Lee's film "Do the Right Thing," artificially intelligent systems have a hard time knowing what to do in all circumstances. Classical theories of perfect rationality prescribe the "right thing" for any occasion, but no finite agent can compute their prescriptions fast enough. In Do the Right Thing, the authors argue that a new theoretical foundation for artificial intelligence can be constructed in which rationality is a property of "programs" within a finite architecture, and their behavior over time in the task environment, rather than a property of individual decisions. Do the Right Thing suggests that the rich structure that seems to be exhibited by humans, and ought to be exhibited by AI systems, is a necessary result of the pressure for optimal behavior operating within a system of strictly limited resources. It provides an outline for the design of new intelligent systems and describes theoretical and practical tools for bringing about intelligent behavior in finite machines. The tools are applied to game planning and realtime problem solving, with surprising results.This book builds on important philosophical and technical work by his coauthor, the late Eric Wefald.
Artificial Intelligence --- Decision Making --- Reasoning --- Computers --- Education --- Philosophy
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