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Following the style of Galileo's Dialogue on the Two Chief World Systems, and addressed to readers without specialized knowledge in physics and higher mathematics, this book lets us listen in on an imaginary meeting of the scientists who created classical physics and modern relativity.

How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.

This book shows you — through examples and puzzles and intriguing questions — how to make your computer reason logically. To help you, the book includes a CD-ROM with OTTER, the world's most powerful general-purpose reasoning program. The automation of reasoning has advanced markedly in the past few decades, and this book discusses some of the remarkable successes that automated reasoning programs have had in tackling challenging problems in mathematics, logic, program verification, and circuit design. Because the intended audience includes students and teachers, the book provides many exercises (with hints and also answers), as well as tutorial chapters that gently introduce readers to the field of logic and to automated reasoning in general. For more advanced researchers, the book presents challenging questions, many of which are still unsolved. Contents:The Menu, The Map, and the MagicLearning Logic by ExampleAutomated Reasoning in FullLogic Circuit DesignLogic Circuit ValidationResearch in MathematicsResearch in Formal LogicThe Formal Treatment of Automated ReasoningWos's Biased Guide for the Effective Use of OTTERAn Author's Appraisal of His PapersOpen Questions, Hard Problems, Intriguing ChallengesEpilogue and After-Dinner Liqueur Readership: College students, teachers, researchers and historians of computer science. Keywords:Automated Reasoning;Theorem Proving;Automated Deduction;Logic;Mathematics;Computing;Artificial Intelligence;Open Questions;Research Topics;OTTER