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The Genesis of Logic addresses the principles of common-sense reasoning, which are employed in everyday decision-making processes and extend beyond deductive reasoning alone. Linked to language, logic inherits its flexibility. These are a few laws, the'formal skeleton of reasoning,'based on the relationship of linguistic inference that, while needing to be represented in each context, allow for the consideration of non-comparable, orthogonal statements. By facilitating deduction and abduction, speculation emerges as a fundamental intellectual operation. As a whole, this work offers a new genetic-evolutionary perspective to reconsider Logic, a panoramic outlook that examines laws outside the skeleton as local laws, necessary for the validity of specialized reasoning. It moves away from the rigid reticular structure of sets of statements and views induction as the search for speculations, non-monotonic reasoning as speculative, and conjecture, only proven in finite Boolean algebras,that reasoning involves following paths of inference in a zigzag pattern, alternating between deduction and abduction.

This unique textbook, in contrast to a standard logic text, provides the reader with a logic that actually can be used in practice to express and reason about mathematical ideas.The book is an introduction to simple type theory, a classical higher-order version of predicate logic that extends first-order logic. It presents a practice-oriented logic called Alonzo that is based on Alonzo Church's formulation of simple type theory known as Church's type theory. Unlike traditional predicate logics, Alonzo admits undefined expressions. The book illustrates, using Alonzo, how simple type theory is suited ideally for reasoning about mathematical structures and constructing libraries of mathematical knowledge.Topics and features:Offers the first book-length introduction to simple type theory as a predicate logicProvides the reader with a logic that is close to mathematical practicePresents the tools needed to build libraries of mathematical knowledgeEmploys two semantics, one for mathematics and one for logicEmphasizes the model-theoretic view of predicate logicIncludes several important topics, such as definite description and theory morphisms, not usually found in standard logic textbooksAimed at students of computing and mathematics at the graduate or upper-undergraduate level, this book is also well-suited for mathematicians, computing professionals, engineers, and scientists who need a practical logic for expressing and reasoning about mathematical ideas.William M. Farmer is a Professor in the Department of Computing and Software at McMaster University in Hamilton, Ontario, Canada.

This book analyses the role of diagrammatic reasoning in Plato's philosophy: the readers will realize that Plato, describing the stages of human cognitive development using a diagram, poses a logic problem to stimulate the general reasoning abilities of his readers. Following the examination of mental models in this book, the readers will reflect on what inferences can be useful to approach this kind of logic problem. Plato calls for a collaboration between writer and readers. In this book the readers will examine the connection between diagrams and discovery, realizing the important epistemic role of visualization. They will recognize the crucial role that diagrams play in problem solving. The logic problem elaborated by Plato is addressed considering the epistemic function of mental models. These models introduce to an advanced stage of cognitive development, in which reasoning uses in its investigations a higher-level of mathematical complexity, represented by structuralism.

This book addresses controversies concerning the epistemological foundations of data science: Is it a genuine science? Or is data science merely some inferior practice that can at best contribute to the scientific enterprise, but cannot stand on its own? The author proposes a coherent conceptual framework with which these questions can be rigorously addressed. Readers will discover a defense of inductivism and consideration of the arguments against it: an epistemology of data science more or less by definition has to be inductivist, given that data science starts with the data. As an alternative to enumerative approaches, the author endorses Federica Russo's recent call for a variational rationale in inductive methodology. Chapters then address some of the key concepts of an inductivist methodology including causation, probability and analogy, before outlining an inductivist framework. The inductivist framework is shown to be adequate and useful for an analysis of the epistemological foundations of data science. The author points out that many aspects of the variational rationale are present in algorithms commonly used in data science. Introductions to algorithms and brief case studies of successful data science such as machine translation are included. Data science is located with reference to several crucial distinctions regarding different kinds of scientific practices, including between exploratory and theory-driven experimentation, and between phenomenological and theoretical science. Computer scientists, philosophers and data scientists of various disciplines will find this philosophical perspective and conceptual framework of great interest, especially as a starting point for further in-depth analysis of algorithms used in data science.

This collection of essays examines the key achievements and likely developments in the area of automated reasoning. In keeping with the group ethos, Automated Reasoning is interpreted liberally, spanning underpinning theory, tools for reasoning, argumentation, explanation, computational creativity, and pedagogy. Wider applications including secure and trustworthy software, and health care and emergency management. The book starts with a technically oriented history of the Edinburgh Automated Reasoning Group, written by Alan Bundy, which is followed by chapters from leading researchers associated with the group. Mathematical Reasoning: The History and Impact of the DReaM Group will attract considerable interest from researchers and practitioners of Automated Reasoning, including postgraduates. It should also be of interest to those researching the history of AI.

Can we change the minds of science deniers? Encounters with flat earthers, anti-vaxxers, coronavirus truthers, and others.“Climate change is a hoax—and so is coronavirus.” “Vaccines are bad for you.” These days, many of our fellow citizens reject scientific expertise and prefer ideology to facts. They are not merely uninformed—they are misinformed. They cite cherry-picked evidence, rely on fake experts, and believe conspiracy theories. How can we convince such people otherwise? How can we get them to change their minds and accept the facts when they don't believe in facts? In this book, Lee McIntyre shows that anyone can fight back against science deniers, and argues that it's important to do so. Science denial can kill.Drawing on his own experience—including a visit to a Flat Earth convention—as well as academic research, McIntyre outlines the common themes of science denialism, present in misinformation campaigns ranging from tobacco companies'denial in the 1950s that smoking causes lung cancer to today's anti-vaxxers. He describes attempts to use his persuasive powers as a philosopher to convert Flat Earthers; surprising discussions with coal miners; and conversations with a scientist friend about genetically modified organisms in food. McIntyre offers tools and techniques for communicating the truth and values of science, emphasizing that the most important way to reach science deniers is to talk to them calmly and respectfully—to put ourselves out there, and meet them face to face.

This volume reflects the ‘philosophy of science in practice'approach and takes a fresh look at traditional philosophical problems in the context of natural, social, and health research. Inspired by the work of Nancy Cartwright that shows how the practices and apparatuses of science help us to understand science and to build theories in the philosophy of science, this volume critically examines the philosophical concepts of evidence, laws, causation, and models and their roles in the process of scientific reasoning. Each chapter is an important one in the philosophy of science, while the volume as a whole deals with these philosophical concepts in a unified way in the context of actual scientific practice. This volumethus aims to contribute to this new direction in the philosophy of science.​

How can we advance knowledge? Which methods do we need in order to make new discoveries? How can we rationally evaluate, reconstruct and offer discoveries as a means of improving the ‘method'of discovery itself? And how can we use findings about scientific discovery to boost funding policies, thus fostering a deeper impact of scientific discovery itself?The respective chapters in this book provide readers with answers to these questions. They focus on a set of issues that are essential to the development of types of reasoning for advancing knowledge, such as models for both revolutionary findings and paradigm shifts; ways of rationally addressing scientific disagreement, e.g. when a revolutionary discovery sparks considerable disagreement inside the scientific community; frameworks for both discovery and inference methods; and heuristics for economics and the social sciences.

Is critical argumentation an effective way to overcome disagreement? And does the exchange of arguments bring opponents in a controversy closer to the truth? This study provides a new perspective on these pivotal questions. By means of multi-agent simulations, it investigates the truth and consensus-conduciveness of controversial debates. The book brings together research in formal epistemology and argumentation theory. Aside from its consequences for discursive practice, the work may have important implications for philosophy of science and the way we construe scientific rationality as well.

The work of Galileo has long been important not only as a foundation of modern physics but also as a model - and perhaps the paradigmatic model - of scientific method, and therefore as a leading example of scientific rationality. However, as we know, the matter is not so simple. The range of Galileo readings is so varied that one may be led to the conclusion that it is a case of chacun a son Galileo; that here, as with the Bible, or Plato or Kant or Freud or Finnegan's Wake, the texts themselves underdetermine just what moral is to be pointed. But if there is no canonical reading, how can the texts be taken as evidence or example of a canonical view of scientific rationality, as in Galileo? Or is it the case, instead, that we decide a priori what the norms of rationality are and then pick through texts to fmd those which satisfy these norms? Specifically, how and on what grounds are we to accept or reject scientific theories, or scientific reasoning? If we are to do this on the basis of historical analysis of how, in fact, theories came to be accepted or rejected, how shall we distinguish'is'from'ought'? What follows (if anything does) from such analysis or reconstruction about how theories ought to be accepted or rejected? Maurice Finocchiaro's study of Galileo brings an important and original approach to the question of scientific rationality by way of a systematic read­

Analogy is the core of all thinking. This is the simple but unorthodox premise that Pulitzer Prize -- winning author Douglas Hofstadter and French psychologist Emmanuel Sander defend in their new work. Hofstadter has been grappling with the mysteries of human thought for over thirty years. Now, with his trademark wit and special talent for making complex ideas vivid, he has partnered with Sander to put forth a highly novel perspective on cognition. We are constantly faced with a swirling and intermingling multitude of ill-defined situations. Our brain's job is to try to make sense of this unpredictable, swarming chaos of stimuli. How does it do so? The ceaseless hail of input triggers analogies galore, helping us to pinpoint the essence of what is going on. Often this means the spontaneous evocation of words, sometimes idioms, sometimes the triggering of nameless, long-buried memories. Why did two-year-old Camille proudly exclaim,'I undressed the banana!'? Why do people who hear a story often blurt out,'Exactly the same thing happened to me!'when it was a completely different event? How do we recognize an aggressive driver from a split-second glance in our rearview mirror? What in a friend's remark triggers the offhand reply,'That's just sour grapes'? What did Albert Einstein see that made him suspect that light consists of particles when a century of research had driven the final nail in the coffin of that long-dead idea? The answer to all these questions, of course, is analogy-making -- the meat and potatoes, the heart and soul, the fuel and fire, the gist and the crux, the lifeblood and the wellsprings of thought. Analogy-making, far from happening at rare intervals, occurs at all moments, defining thinking from top to toe, from the tiniest and most fleeting thoughts to the most creative scientific insights. Like Gö, Escher, Bach before it, Surfaces and Essences will profoundly enrich our understanding of our own minds. By plunging the reader into an extraordinary variety of colorful situations involving language, thought, and memory, by revealing bit by bit the constantly churning cognitive mechanisms normally completely hidden from view, and by discovering in them one central, invariant core -- the incessant, unconscious quest for strong analogical links to past experiences -- this book puts forth a radical and deeply surprising new vision of the act of thinking.

The incredible achievements of modern scientific theories lead most of us to embrace scientific realism: the view that our best theories offer us at least roughly accurate descriptions of otherwise inaccessible parts of the world like genes, atoms, and the big bang. In Exceeding Our Grasp, Stanford argues that careful attention to the history of scientific investigation invites a challenge to this view that is not well represented in contemporary debates about the nature of the scientific enterprise. The historical record of scientific inquiry, Stanford suggests, is characterized by what he calls the problem of unconceived alternatives. Past scientists have routinely failed even to conceive of alternatives to their own theories and lines of theoretical investigation, alternatives that were both well-confirmed by the evidence available at the time and sufficiently serious as to be ultimately accepted by later scientific communities. Stanford supports this claim with a detailed investigation of the mid-to-late 19th century theories of inheritance and generation proposed in turn by Charles Darwin, Francis Galton, and August Weismann. He goes on to argue that this historical pattern strongly suggests that there are equally well-confirmed and scientifically serious alternatives to our own best theories that remain currently unconceived. Moreover, this challenge is more serious than those rooted in either the so-called pessimistic induction or the underdetermination of theories by evidence, in part because existing realist responses to these latter challenges offer no relief from the problem of unconceived alternatives itself. Stanford concludes by investigating what positive account of the spectacularly successful edifice of modern theoretical science remains open to us if we accept that our best scientific theories are powerful conceptual tools for accomplishing our practical goals, but abandon the view that the descriptions of the world around us that they offer are therefore even probably or approximately true.

In By Parallel Reasoning Paul Bartha proposes a normative theory of analogical arguments and raises questions and proposes answers regarding (i.) criteria for evaluating analogical arguments, (ii.) the philosophical justification for analogical reasoning, and (iii.) the place of scientific analogies in the context of theoretical confirmation.

In 1986, the emergence of a novel brain disease in British cattle presented a unique challenge to scientists. How that challenge was addressed has been the subject of a public inquiry and numerous academic studies conducted to date. However, none of these investigations has sought to examine the reasoning of scientists during this critical period in the public health of the UK. Using concepts and techniques in informal logic, argumentation and fallacy theory, this study reconstructs and evaluates the reasoning of scientists in the ten-year period between 1986 and 1996. Specifically, a form of presumptive reasoning is described in which extensive use is made of arguments traditionally identified as informal fallacies. In the context of the adverse epistemic conditions that confronted scientists during the BSE epidemic, these arguments were anything but fallacious, serving instead to confer a number of epistemic gains upon scientific inquiry. This book argues for a closer integration of philosophy with public health science, an integration that is exemplified by the case of scientific reasoning during the BSE affair. It will therefore be of interest to advanced students, academics, researchers and professionals in the areas of public health science and epidemiology, as well as philosophical disciplines such as informal logic, argumentation and fallacy theory and epistemology.

A groundbreaking solution to the problem of induction, based on Ayn Rand's theory of concepts. Inspired by and expanding on a series of lectures presented by Leonard Peikoff, David Harriman presents a fascinating answer to the problem of induction-the epistemological question of how we can know the truth of inductive generalizations. Ayn Rand presented her revolutionary theory of concepts in her book Introduction to Objectivist Epistemology. As Dr. Peikoff subsequently explored the concept of induction, he sought out David Harriman, a physicist who had taught philosophy, for his expert knowledge of the scientific discovery process. Here, Harriman presents the result of a collaboration between scientist and philosopher. Beginning with a detailed discussion of the role of mathematics and experimentation in validating generalizations in physics-looking closely at the reasoning of scientists such as Galileo, Kepler, Newton, Lavoisier, and Maxwell-Harriman skillfully argues that the inductive method used in philosophy is in principle indistinguishable from the method used in physics.

Abductive Reasoning: Logical Investigations into Discovery and Explanation is a much awaited original contribution to the study of abductive reasoning, providing logical foundations and a rich sample of pertinent applications. Divided into three parts on the conceptual framework, the logical foundations, and the applications, this monograph takes the reader for a comprehensive and erudite tour through the taxonomy of abductive reasoning, via the logical workings of abductive inference ending with applications pertinent to scientific explanation, empirical progress, pragmatism and belief revision.

Robert Batterman examines a form of scientific reasoning called asymptotic reasoning, arguing that it has important consequences for our understanding of the scientific process as a whole. He maintains that asymptotic reasoning is essential for explaining what physicists call universal behavior. With clarity and rigor, he simplifies complex questions about universal behavior, demonstrating a profound understanding of the underlying structures that ground them. This book introduces a valuable new method that is certain to fill explanatory gaps across disciplines.

The Anatomy of Judgment was first published in 1990. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions.''The Anatomy of Judgment is a unique and valuable contribution to the literature of the social and humanistic contexts for science... The book will illuminate dark corners for any reader, and dozens of interesting points come to light.''--Neil Greenberg, University of Tennessee. Tracing the emergence of science and the social institutions that govern

The study of human judgment and its limitations is essential to an understanding of the processes involved in the acquisition of scientific knowledge. With that end in mind, David Faust has made the first comprehensive attempt to apply recent research on.