Download Free Reliable Reasoning Book in PDF and EPUB Free Download. You can read online Reliable Reasoning and write the review.

The implications for philosophy and cognitive science of developments in statistical learning theory. In Reliable Reasoning, Gilbert Harman and Sanjeev Kulkarni—a philosopher and an engineer—argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors—a central topic in SLT. After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.
This new volume addresses the central questions which surround the process of reasoning. This emerging topic of analytic philosophy intersects with numerous other areas of philosophy, such as epistemology, philosophy of mind, philosophy of language, and metaethics, and also psychological work on reasoning.
Dealing with uncertainty, moving from ignorance to knowledge, is the focus of cognitive processes. Understanding these processes and modelling, designing, and building artificial cognitive systems have long been challenging research problems. This book describes the theory and methodology of a new, scientifically well-founded general approach, and its realization in the form of intelligent systems applicable in disciplines ranging from social sciences, such as cognitive science and sociology, through natural sciences, such as life sciences and chemistry, to applied sciences, such as medicine, education, and engineering. The main subject developed in the book is cognitive reasoning investigated at three levels of abstraction: conceptual, formal, and realizational. The authors offer a model of a cognizing agent for the conceptual theory of cognitive reasoning, and they also present a logically well-founded formal cognitive reasoning framework to handle the various plausible reasoning methods. They conclude with an object model of a cognitive engine. The book is suitable for researchers, scientists, and graduate students working in the areas of artificial intelligence, mathematical logic, and philosophy.
Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing.
Good Reasoning Matters uses an innovative approach to critical thinking by teaching students how to argue effectively rather than just point out the short comings of ineffective arguments.
Too often we're guided by what we last heard, by our friends' approval, by impulse—our desires, our fears. Without reflection. Without even stopping to think. ** In this book you'll learn how to reason and find your way better in life. You'll learn to see the consequences of what you and others say and do. You'll learn to see the assumptions that you and others make. You'll learn how to judge what you should believe. These are the skills we all need to make good decisions. ** Claims. Arguments. Fallacies. Analogies. Generalizing. Cause and Effect. Explanations. These are clearly set out with hundreds of examples from daily life showing how to use them. Illustrations using a cast of cartoon characters make the concepts memorable. And many exercises will help you to check your understanding. ** Truly a book for all—from high school to graduate school, from auto repair to managing a company. How to Reason will help you find a way in life that is clearer and not buffetted by the winds of nonsense and fear. ******* In Reasoning in the Sciences, you'll learn how to use your reasoning skills to understand how scientists make definitions, what an experiment is, what can go wrong with an experiment, how scientists reason with models and theories, what counts as a good explanation in science, and how to distinguish science from magic, religion, and fraud. No background in science is needed, just a healthy appetitite for learning.
Offering an innovative approach to critical thinking, Good Reasoning Matters! identifies the essential structure of good arguments in a variety of contexts and also provides guidelines to help students construct their own effective arguments. In addition to examining the most common features of faulty reasoning--slanting, bias, propaganda, vagueness, ambiguity, and a common failure to consider opposing points of view--the book introduces a variety of argument schemes and rhetorical techniques. This edition adds material on visual arguments and more exercises.
In the 20th century philosophy of mathematics has to a great extent been dominated by views developed during the so-called foundational crisis in the beginning of that century. These views have primarily focused on questions pertaining to the logical structure of mathematics and questions regarding the justi?cation and consistency of mathematics. Paradigmatic in this - spect is Hilbert’s program which inherits from Frege and Russell the project to formalize all areas of ordinary mathematics and then adds the requi- ment of a proof, by epistemically privileged means (?nitistic reasoning), of the consistency of such formalized theories. While interest in modi?ed v- sions of the original foundational programs is still thriving, in the second part of the twentieth century several philosophers and historians of mat- matics have questioned whether such foundational programs could exhaust the realm of important philosophical problems to be raised about the nature of mathematics. Some have done so in open confrontation (and hostility) to the logically based analysis of mathematics which characterized the cl- sical foundational programs, while others (and many of the contributors to this book belong to this tradition) have only called for an extension of the range of questions and problems that should be raised in connection with an understanding of mathematics. The focus has turned thus to a consideration of what mathematicians are actually doing when they produce mathematics. Questions concerning concept-formation, understanding, heuristics, changes instyle of reasoning, the role of analogies and diagrams etc.
The debate between internalism and externalism has become a focal point of attention both in epistemology and in the philosophy of mind and language. Externalism challenges basic traditional internalist conceptions of the nature of knowledge, justification, thought and language. What is at stake, is the very form that theories in epistemology and the philosophy of mind ought to take. This volume is a collection of original contributions of leading international authors reflecting on the present state of the art concerning the exciting controversies between internalism and externalism.