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This book lays out key questions, practical challenges and 'common sense' concerns underlying the incorporation of Common Sense within machine learning algorithms for simulating intelligence, socializing robots, self-driving vehicles, personnel selection, reading, automatic text analysis, and text production.

Commonsense reasoning. --- Artificial intelligence

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This book by one of the world's foremost philosophers in the fields of epistemology and logic offers an account of suppositional reasoning relevant to practical deliberation, explanation, prediction and hypothesis testing. Suppositions made 'for the sake of argument' sometimes conflict with our beliefs, and when they do, some beliefs are rejected and others retained. Thanks to such belief contravention, adding content to a supposition can undermine conclusions reached without it. Subversion can also arise because suppositional reasoning is ampliative. These two types of nonmonotonic logic are the focus of this book. A detailed comparison of nonmonotonicity appropriate to both belief contravening and ampliative suppositional reasoning reveals important differences that have been overlooked.

Commonsense reasoning. --- Conditionals (Logic) --- Hypothesis. --- Induction (Logic) --- Inference. --- Nonmonotonic reasoning. --- Conditionals (Logic). --- Induction (Logic). --- Commonsense reasoning --- Hypothesis --- Inference --- Nonmonotonic reasoning --- Non-monotonic reasoning --- Reasoning --- Ampliative induction --- Induction, Ampliative --- Inference (Logic) --- Inductive logic --- Logic, Inductive --- Logic --- Assumption --- Supposition --- Science --- Conditional statements (Logic) --- Grammar, Comparative and general --- Common sense reasoning --- Methodology --- Induction (logique) --- Arts and Humanities --- Philosophy --- Philosophie --- Artificial intelligence --- Logique --- Knowledge representation

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Artificial intelligence --- -Connectionism --- -Connexionism --- Cognition --- 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 --- Data processing --- -Congresses --- Gezond verstand --- Artificial intelligence. Robotics. Simulation. Graphics --- Commonsense reasoning --- Common sense reasoning --- Reasoning --- Artificial intelligence. --- Commonsense reasoning. --- Connectionism --- Congresses. --- Common sense. --- Reasoning.

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“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.

Artificial intelligence. --- Neurosciences. --- Natural language processing (Computer science) --- Logic. --- Intellect. --- Inference. --- AI and futurism. --- AI and innovation. --- AI and neuroscience. --- AI and superintelligence. --- AI and the Turing test. --- AI hype. --- AI winter. --- commonsense reasoning. --- limitations of AI. --- natural language understanding. --- the future of AI. --- the problem with AI.

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This book constitutes the thoroughly refereed post-workshop proceedings of three workshops held in conjunction with the 10th Australian Joint Conference on Artificial Intelligence in Perth, Australia, in December 1997. The 17 revised full papers presented were carefully reviewed for inclusion in the book. The book is divided into sections on formal methods of agency, reasoning agents, communication and coordination, social interaction, and practical issues for distributed artificial intelligence systems.

Distributed artificial intelligence --- Intelligent agents (Computer software) --- Commonsense reasoning --- Common sense reasoning --- Computer science. --- Computer communication systems. --- Software engineering. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computer Communication Networks. --- Software Engineering. --- 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 --- Computer software engineering --- Engineering --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Informatics --- Science --- Distributed processing --- Congresses --- Artificial Intelligence. --- Distributed artificial intelligence - Congresses --- Intelligent agents (Computer software) - Congresses --- Commonsense reasoning - Congresses --- Computer networks.