"According to Bayesian epistemology, rational learning from experience is consistent learning, that is learning should incorporate new information consistently into one's old system of beliefs. Simon M. Huttegger argues that this core idea can be transferred to situations where the learner's informational inputs are much more limited than Bayesianism assumes, thereby significantly expanding the reach of a Bayesian type of epistemology. What results from this is a unified account of probabilistic learning in the tradition of Richard Jeffrey's 'radical probabilism'. Along the way, Huttegger addresses a number of debates in epistemology and the philosophy of science, including the status of prior probabilities, whether Bayes' rule is the only legitimate form of learning from experience, and whether rational agents can have sustained disagreements. His book will be of interest to students and scholars of epistemology, of game and decision theory, and of cognitive, economic, and computer sciences"-- Provided by publisher. "Learning is something we are all very familiar with. As children we learn to recognize faces, to walk, to speak, to climb trees and ride bikes, and so many other things that it would be a hopeless task to continue the list. Later we learn how to read and write; we learn arithmetic, calculus, and foreign languages; we learn how to cook spaghetti, how to drive a car, or what's the best response to telemarketing calls. Even as adults, when many of our beliefs have become entrenched and our behaviors often is habitual, there are new alternatives to explore if we wish to do so; and sometimes we even may revise long held beliefs or change our conduct based on something we have learned"-- Provided by publisher.
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