دانلود کتاب قوانین تفکر – جستجو برای یک نظریه ریاضی ذهن

Everyone has a basic understanding of how the physical world works. We learn about physics and chemistry in school, letting us explain the world around us in terms of concepts like force, acceleration, and gravity—the Laws of Nature. But we don’t have the same fluency with the concepts needed to understand the world inside us—the Laws of Thought. You have probably heard of Newton’s universal law of gravitation. But you might not have heard of Shepard’s universal law of generalization—a simple principle that describes the behavior of any intelligent organism, anywhere in the universe. While the story of how mathematics has been used to reveal the mysteries of the external world is familiar to anybody who has taken even a casual interest in science, the story of how it has been used to study our internal world is not. This book tells that story. A little over three hundred years ago, a small group of philosophers and mathematicians began to pull together the threads that make up modern science. They developed a keen sense of observation, a talent for conducting experiments, and a new set of tools for expressing mathematical theories. Over the following centuries, observation, experiment, and mathematics have been combined to reveal both the smallest and the largest things in the physical universe in ever-increasing detail. But those philosophers and mathematicians weren’t just interested in the physical universe. They were also interested in the mind, and they wanted to use the same mathematical tools to study it. Thomas Hobbes wrote about the possibility of understanding “ratiocination” as “calculation,” asking whether we might imagine thoughts being added and subtracted. René Descartes imagined numbers being assigned to thoughts in much the same way that they are assigned to collections of physical objects. Gottfried Wilhelm Leibniz spent his life trying, and ultimately failing, to find a way to use arithmetic to describe human reason. The first success in using mathematics to analyze thought wouldn’t appear until the middle of the nineteenth century, when George Boole cracked the problem that Leibniz hadn’t been able to solve by coming up with a new kind of algebra. That first success had far-reaching consequences, leading to the development of formal logic and computers. The first attempts to evaluate mathematical theories of thought by comparing them to human behavior wouldn’t appear until the middle of the twentieth century, in the Cognitive Revolution that launched the field of cognitive science—the interdisciplinary science of the mind. Cognitive scientists have since come to recognize the limits of formal logic as a model of human cognition, and have developed completely new mathematical approaches—artificial neural networks, which illustrate the power of continuous representations and statistical learning, and Bayesian models, which reveal how to capture prior knowledge and deal with uncertainty. Each has something to offer for understanding the mind. In the twenty-first century, knowing the Laws of Thought is just as important to scientific literacy as knowing the Laws of Nature. Artificial intelligence systems demonstrate on a daily basis that yet another aspect of thought and language can be emulated by machines, pushing us to reconsider the way we think about ourselves. Understanding human minds and how much of them can be automated becomes critical as we plan our careers and think about the world that our children will occupy. By the end of this book you will know the basic principles behind how modern artificial intelligence systems work, and know exactly where they are likely to continue to fall short of human abilities.