<i>The Mathematical Theory of Communication</i>
Physics Today · 1950
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Artificial intelligence: a modern approach
The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.
Toward an epistemology of physics
The aim of this work is twofold: to understand the intuitive sense of mechanism that accounts for commonsense predictions, expectations, explanations, and judg-ments of plausibility concerning mechanically causal situations and to understand how those intuitive ideas contribute to and develop into school physics. To facili-tate this, I provide a framework for describing and correlating characteristics of weakly organized knowledge systems. The framework is aimed at answering, at a coarse level of detail, a set of questions central to a full theory of knowledge: What are the elements of knowledge; how do they arise; what level and kind of systematicity exists; how does the system as a whole evolve; and what can be said about the underlying cognitive mechanisms that are responsible for the normal oper-ation of the system and its evolution? The empirical base is a set of clinical interviews of undergraduate physics stu-dents trying to solve a set of specially designed problems. Observations from this core and from the existing literature are extended with informal data and synthe-sized using the general framework.
The Structure of Scientific Revolutions
A good book may have the power to change the way we see the world, but a great book actually becomes part of our daily consciousness, pervading our thinking to the point that we take it for granted, and we forget how provocative and challenging its ideas once were-and still are. The Structure of Scientific Revolutions is that kind of book. When it was first published in 1962, it was a landmark event in the history and philosophy of science. And fifty years later, it still has many lessons to teach. With The Structure of Scientific Revolutions, Kuhn challenged long-standing linear notions of scientific progress, arguing that transformative ideas don't arise from the day-to-day, gradual process of experimentation and data accumulation, but that revolutions in those breakthrough moments that disrupt accepted thinking and offer unanticipated ideas, occur outside of normal science, as he called it. Though Kuhn was writing when physics ruled the sciences, his ideas on how scientific revolutions bring order to the anomalies that amass over time in research experiments are still instructive in our biotech age. This new edition of Kuhn's essential work in the history of science includes an insightful introductory essay by Ian Hacking that clarifies terms popularized by Kuhn, including paradigm and incommensurability, and applies Kuhn's ideas to the science of today. Usefully keyed to the separate sections of the book, Hacking's essay provides important background information as well as a contemporary context. Newly designed, with an expanded index, this edition will be eagerly welcomed by the next generation of readers seeking to understand the history of our perspectives on science.