In this paper we will show Peirce’s distinction between deduction, induction and abduction. The aim of the paper is to show how Peirce changed his views on the subject, from an understanding of deduction, induction and hypotheses as types of reasoning to understanding them as stages of inquiry very tightly connected. In order to get a better understanding of Peirce’s originality on this, we show Peirce’s distinctions between qualitative and quantitative induction and between theorematical and corollarial deduction, passing then (...) to the distinction between mathematics and logic. In the end, we propose a sketch of a comparison between Peirce and Whitehead concerning the two thinkers’ view of mathematics, hoping that this could point to further inquiries. (shrink)

Reasoning over our knowledge bases and theories often requires non-deductive inferences, especially – but by no means only – when commonsense reasoning is the case, i.e. when practical agency is called for. This kind of reasoning can be adequately formalized via the notion of supraclassical consequence, a non-deductive consequence tightly associated with default and non-monotonic reasoning and featuring centrally in abductive, inductive, and probabilistic logical systems. In this paper, we analyze core concepts and problems of (...) these systems in the light of supraclassical consequence. (shrink)

Abduction, deduction and induction are different forms of inference in science. However, only a few attempts have been made to introduce the idea of abductive reasoning as an extended way of thinking about clinical practice in nursing research. The aim of this paper was to encourage critical reflections about abductive reasoning based on three empirical examples from nursing research and includes three research questions on what abductive reasoning is, how the process has taken place, (...) and how knowledge about abductive reasoning based on the examples can inform nursing research and clinical practice. The study has a descriptive and explorative approach using a convenience sample of three empirical studies from nursing research. The three studies illustrate different ways to enter the abductive reasoning process in steps. They represent new caring models, which offer visual and cognitive maps for expanding nursing research, education and thus informing care. Therefore, we suggest that abductive reasoning may be beneficial for different ways of knowing and demonstrates scientific innovation to shed new light on health phenomena, which can help researchers and practitioners to gain a broader and deeper understanding of nursing care inquiry. However, more studies are needed to broaden this scope. (shrink)

Abduction, deduction and induction describe forms of reasoning. Deduction and induction are discussed in the nursing literature. However, abduction has been largely neglected by nurse scholars. In this paper it is proposed that abduction may play a part in qualitative data analysis – specifically, in the identification of themes, codes, and categories. Abduction is not, in research, restricted to or associated with any particular methodology. Nevertheless, situating abduction in qualitative research facilitates the identification of three interlinked issues. First, it (...) is suggested that abductively derived claims require support from deductive and inductively sourced evidence if they are to ‘hold’ and, yet, in qualitative research this is clearly problematic. Second, difficulties in choosing between alternative plausible hypotheses are explored through an examination of the ‘generality problem’. Third, the role of background and auxiliary theories in adjudicating between hypothesis options is discussed. It is argued that if qualitative researchers utilize abductive inference in the manner suggested, then the peculiarly fallible nature of abduction must be acknowledged and, in consequence, the action guiding potential of qualitative research findings is compromised. (shrink)

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from (...) developments made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration. (shrink)

Essential to Peirce's distinction among three kinds of reasoning, deduction, induction and abduction, is the claim that each is correlated to a unique species of validity irreducible to that of the others. In particular, abductive validity cannot be analyzed in either deductive or inductive terms, a consequence of considerable importance for the logical and epistemological scrutiny of scientific methods. But when the full structure of abductive argumentation — as viewed by the mature Peirce — is clarified, every (...) inferential step in the process can be seen to dissolve into familiar forms of deductive and inductive reasoning. Specifically, the final stage is a special type of practical inference which, if correct, is deductively valid, while the creative phase, surprisingly, is not inferential at all. In neither is abduction a type of inference to the best explanation. The result is a major reassessment of the relevance of Peirce's views to contemporary methodological studies. (shrink)

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from (...) developments made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration. (shrink)

Inference to the best explanation (IBE) is considered to be the main means of discovery and justification of scientific hypotheses and theories. The article investigates this inference and its relationship to the main kinds of inference: deduction, induction and abduction. IBE has an abductive inference mechanism, but, contrary to abduction, infers not a possible, but a true conclusion. IBE is an inductive inference, because it is underdetermined by the rules of deduction and by evidence. The article claims that despite (...) its abductive and inductive features which demonstrate that it is not and cannot be deductive inference, IBE nevertheless makes pretense to an absolute truth of its inference, i.e. claims for an almost deductive validity. (shrink)

We examine Charles S. Peirce's mature views on the logic of science, especially as contained in his later and still mostly unpublished writings. We focus on two main issues. The first concerns Peirce's late conception of retroduction. Peirce conceived inquiry as performed in three stages, which correspond to three classes of inferences: abduction or retroduction, deduction, and induction. The question of the logical form of retroduction, of its logical justification, and of its methodology stands out as the three major threads (...) in his later writings. The other issue concerns the second stage of scientific inquiry, deduction. According to Peirce's later formulation, deduction is divided not only into two kinds but also into two sub-stages: logical analysis and mathematical reasoning, where the latter is either corollarial or theorematic. Save for the inductive stage, which we do not address here, these points cover the essentials of Peirce's latest thinking on the l.. (shrink)

Automated Software Testing (AST) using Model Checking is in this article epistemologically analysed in order to argue in favour of a model-based reasoning paradigm in computer science. Preliminarily, it is shown how both deductive and inductive reasoning are insufficient to determine whether a given piece of software is correct with respect to specified behavioural properties. Models algorithmically checked in Model Checking to select executions to be observed in Software Testing are acknowledged as analogical models which establish isomorphic relations (...) with the target system’s data set. Analogical models developed in AST are presented as abductive models providing hypothetical explanations to observed executions. The model assumption—algorithmic check—software testing process is understood as the abduction—deduction—induction process defining the selective abduction and turned to isolate a set of model-based hypotheses concerning the target system behaviours. A manipulative abduction process is finally recognized in the practice of adapting, abstracting and refining models that do not provide successful predictions. (shrink)

The paper begins by focusing the basic idea that Gestalt phenomena belong not only to the realm of perception but to the realm of inference. It is shown that Gestalt effects often occur both in counterfactual and in ampliative – i.e. inductive and abductive – reasoning. The main thesis of the paper is that the common feature of such forms of non-deductive reasoning is provided by a rational selection between incompatible conclusions, where rationality lies in the choice (...) of the alternative which preserves the maximum of background information. It is also stressed a distinction between a weak and a strong notion of incompatibility. Such distinction may help in giving account of some alleged Gestalt phenomena which have been recognized in theory construction and theory change. (shrink)

Inquisitiveness has been found to be a characteristic of successful global managers. The paper distinguishes inquisitiveness from purposeless curiosity andshows that it is a virtue. It suggests that the practice of inquisitiveness is akin to abduction, the method of reasoning described by Charles S. Peirce distinct from deduction and induction, and essential to creativity. It then suggests that an enhanced capacity for inquisitiveness and abduction will increase the capacity for moral imagination and hence improve moral decision-making (and perhaps moral (...) behaviour). (shrink)

This paper is an effort to realize and explore the connections that exist between nonmonotonic logic and confirmation theory. We pick up one of the most wide-spread nonmonotonic formalisms – default logic – and analyze to what extent and under what adjustments it could work as a logic of induction in the philosophical sense. By making use of this analysis, we extend default logic so as to make it able to minimally perform the task of a logic of induction, having (...) as a result a system which we believe has interesting properties from the standpoint of theory of confirmation. It is for instance able to represent chains of inductive rules as well as to reason paraconsistently on the conclusions obtained from them. We then use this logic to represent some traditional ideas concerning confirmation theory, in particular the ones proposed by Carl Hempel in his classical paper "Studies in the Logic of Confirmation" of 1945 and the ones incorporated in the so-called abductive and hy-pothetico-deductive models. (shrink)

Essentialism is often criticized for producing biased behavior. Because it is a view through which people attempt to grasp the essence of things, it appears contradictory that essentialism might result in distortions of reality. Somewhere within essentialist cognitive processes there must be mistakes or omissions that fail to capture reality correctly. In this paper, I treat essentialization as an abductive reasoning process, as a hypothesis, that explains particular characteristics of people on the basis of category membership alone. Besides (...) essentialization, essentialist reasoning can also include deductive and inductive processes that aim at elaborating and testing initial hypotheses. Therefore, essentialist beliefs can be built by essentialization and hypotheses alone or they can be the product of more elaborate reasoning. The relationship of essentialization and general essentialist reasoning to truth and knowledge is discussed. (shrink)

I begin with a typology of reasoning and cross it with types of processes. I demonstrate that the thrust of Plato’s Republic is theory-building. This involves the critical and dialectic processes which are paradigms of Platonic methodology. Book I displays abductive analogical reasoning joined by an induction that is embedded in a deduction; hence there is a deduction–induction–abduction chain. In Book VI, Plato constructs a visual model of the divided line, which also displays model-based and abductive (...) hypothesis generation that is essential to theory building. Book VII provides an abductive metaphor model of the allegory of the cave. Both models depict degrees of reality and the ascendency of knowledge. The multimodal model-based allegory has far reaching applications from criminal justice to information systems. I conclude by capturing the narrative of the Republic as a critical and dialectic process of theory building using deductive–inductive–abductive chains, an abductive visual model and an abductive metaphor model. Hence, the Republic is simultaneously a masterpiece of deductive reasoning and a marvel of complex model-based abduction, involving visual models, analogies and metaphors. (shrink)

Mercier & Sperber (M&S) argue for their argumentative theory in terms of communicative abilities. Insights can be gained by extending the discussion beyond human reasoning to rodent and robot navigation. The selection of arguments and conclusions that are mutually reinforcing can be cast as a form of abductive reasoning that I argue underlies the construction of cognitive maps in navigation tasks.

Journal Name: Semiotica Issue: Ahead of print.

The roles of abductive inference in dynamic heuristics allows scientific methodologies to test novel explanations for the world’s ways. Deliberate reasoning often follows abductive patterns, as well as patterns dominated by deduction and induction, but complex mixtures of these three modes of inference are crucial for scientific explanation. All possible mixed inferences are formulated and categorized using a novel typology and nomenclature. Twenty five possible combinations among abduction, induction, and deduction are assembled and analyzed in order of (...) complexity. There are five primary categories for sorting these inferential procedures: fallacies, non-scientific procedures, quasi-scientific procedures, scientific procedures, and scientific heuristics. (shrink)

While inductive and deductive reasoning are considered distinct logical and psychological processes, little is known about their respective neural basis. To address this issue we scanned 16 subjects with fMRI, using an event-related design, while they engaged in inductive and deductive reasoning tasks. Both types of reasoning were characterized by activation of left lateral prefrontal and bilateral dorsal frontal, parietal, and occipital cortices. Neural responses unique to each type of reasoning determined from the Reasoning Type (...) by Task interaction indicated greater involvement of left inferior frontal gyrus in deduction than induction, while left dorsolateral prefrontal gyrus showed greater activity during induction than deduction. This pattern suggests a dissociation within prefrontal cortex for deductive and inductive reasoning. (shrink)

This interdisciplinary work is a collection of major essays on reasoning: deductive, inductive, abductive, belief revision, defeasible, cross cultural, conversational, and argumentative. They are each oriented toward contemporary empirical studies. The book focuses on foundational issues, including paradoxes, fallacies, and debates about the nature of rationality, the traditional modes of reasoning, as well as counterfactual and causal reasoning. It also includes chapters on the interface between reasoning and other forms of thought. In general, this last (...) set of essays represents growth points in reasoning research, drawing connections to pragmatics, cross-cultural studies, emotion and evolution. (shrink)

This paper discusses abductive reasoning---that is, reasoning in which explanatory hypotheses are formed and evaluated. First, it criticizes two recent formal logical models of abduction. An adequate formalization would have to take into account the following aspects of abduction: explanation is not deduction; hypotheses are layered; abduction is sometimes creative; hypotheses may be revolutionary; completeness is elusive; simplicity is complex; and abductive reasoning may be visual and non-sentential. Second, in order to illustrate visual aspects of (...) hypothesis formation, the paper describes recent work on visual inference in archaeology. Third, in connection with the evaluation of explanatory hypotheses, the paper describes recent results on the computation of coherence. (shrink)

In informal terms, abductive reasoning involves inferring the best or most plausible explanation from a given set of facts or data. It is a common occurrence in everyday life and crops up in such diverse places as medical diagnosis, scientific theory formation, accident investigation, language understanding, and jury deliberation. In recent years, it has become a popular and fruitful topic in artificial intelligence research. This volume breaks new ground in the scientific, philosophical, and technological study of abduction. It (...) presents new ideas about inferential and information-processing foundations for knowledge and certainty. The authors argue that knowledge arises from experience by processes of abductive inference, in contrast to the view that it arises non-inferentially, or that deduction and inductive generalization are enough to account for knowledge. Much AI research is hypothetical, so the importance of this book is that it reports key discoveries about abduction that have been made as a result of designing, building, testing, and analyzing actual working knowledge-based systems for medical diagnosis and other abductive tasks. The book tells the story of six generations of increasingly sophisticated generic abduction machines, RED-1, RED-2, PEIRCE, MDX2, TIPS, QUAWDS, and the discovery of reasoning strategies that make it computationally feasible to form well-justified composite explanatory hypotheses, despite the threat of combinatorial explosion. The final chapter argues that perception is logically abductive and presents a layered-abduction computational model of perceptual information processing. This book will be of great interest to researchers in AI, cognitive science, and philosophy of science. (shrink)

In this paper, we propose an argumentation formalism that allows for both deductive and abductive argumentation, where ‘deduction’ is used as an umbrella term for both defeasible and strict ‘forward’ inference. Our formalism is based on an extended version of our previously proposed information graph formalism, which provides a precise account of the interplay between deductive and abductive inference and causal and evidential information. In the current version, we consider additional types of information such as abstractions which allow (...) domain experts to be more expressive in stating their knowledge, where we identify and impose constraints on the types of inferences that may be performed with the different types of information. A new notion of attack is defined that captures a crucial aspect of abductive reasoning, namely that of competition between abductively inferred alternative explanations. Our argumentation formalism generates an abstract argumentation framework and thus allows arguments to be formally evaluated. We prove that instantiations of our argumentation formalism satisfy key rationality postulates. (shrink)

In this paper I want to cast doubt on the claim that there is a legitimate process of reasoning to the best explanation which can serve as an alternative to either straightforward inductive reasoning or a combination of inductive and deductive reasoning. I shall argue a) that paradigmatic cases of acceptable arguments to the best explanation must be considered enthymemes and b) that when the suppressed premises are made explicit we have all of the premises we need (...) to present either a straightforward inductive argument or an argument employing both induction and deduction. (shrink)

Ever since Aristotle it has been accepted that there exists a combination of inductive and deductive reasoning and a sort of unified inductive-deductive methodology. If one analyzes the procedures and logic of scientific explanation and the methods of generating and justifying scientific knowledge, one recognizes the prototype of philosophy of science found in Aristotle’s inductive and deductive procedure that is described in his Posterior Analytics, Physics and Metaphysics, where heviewed scientific inquiry as a progression from observations to general principles (...) and back to observation. He maintained that the scientist should induce explanatory principles from the phenomena to be explained, and then deduce statements about the phenomena from premisses which include these principles. (shrink)

Ever since Aristotle it has been accepted that there exists a combination of inductive and deductive reasoning and a sort of unified inductive-deductive methodology. If one analyzes the procedures and logic of scientific explanation and the methods of generating and justifying scientific knowledge, one recognizes the prototype of philosophy of science found in Aristotle’s inductive and deductive procedure that is described in his Posterior Analytics, Physics and Metaphysics, where heviewed scientific inquiry as a progression from observations to general principles (...) and back to observation. He maintained that the scientist should induce explanatory principles from the phenomena to be explained, and then deduce statements about the phenomena from premisses which include these principles. (shrink)

The articles in this volume deal with the main inferential methods that can be applied to different kinds of experimental evidence.

This paper argues that Umberto Eco had a sophisticated theory of abductive reasoning and that this theory is fundamentally akin to Peirce’s both in the analysis and in the justification of this kind of reasoning. The first section expounds the essentials of Peirce’s theory of abduction, and explains how Peirce moved from seeing abduction as a kind of reasoning to seeing it as a stage of the larger process of inquiry. The second section deals with one (...) of Eco’s paradigmatic examples of abduction, i.e., William of Baskerville’s abduction concerning the horse Brunellus in the overture of The Name of the Rose, and shows that, just like in Peirce’s three-stages model of inquiry, William’s abductions are verified by means of deduction and induction. The third section examines the problem of the justification of abductive reasoning, and argues that both Peirce and Eco solved this problem through the idea that the justification of abduction is itself abductive (meta-abduction in Eco, ur-abduction in Peirce). (shrink)

Scientific literacy is an essential aspect of an undergraduate education. Recipes for Science responds to this need by providing an accessible introduction to the nature of science and scientific methods appropriate for any beginning college student. The book is adaptable to a wide variety of different courses, such as introductions to scientific reasoning, methods courses in scientific disciplines, science education, and philosophy of science. -/- Recipes for Science ​​was first published in 2018, and a thoroughly revised second edition was (...) published in 2024. Special features include contemporary and historical case studies from many fields of physical, life, and social sciences; visual aids to clarify and illustrate ideas; text boxes to explore related topics; plenty of exercises to support student recall and application of concepts; suggestions for further readings at the end of each chapter; a glossary with helpful definitions of key terms; and a companion website with course syllabi, PowerPoint presentations, additional exercises, and original short videos on key topics. (shrink)

The roles of abductive inference in dynamic heuristics allows scientific methodologies to test novel explanations for the world’s ways. Deliberate reasoning often follows abductive patterns, as well as patterns dominated by deduction and induction, but complex mixtures of these three modes of inference are crucial for scientific explanation. All possible mixed inferences are formulated and categorized using a novel typology and nomenclature. Twenty five possible combinations among abduction, induction, and deduction are assembled and analyzed in order of (...) complexity. There are five primary categories for sorting these inferential procedures: fallacies, non-scientific procedures, quasi-scientific procedures, scientific procedures, and scientific heuristics. (shrink)

In this paper, we set out to investigate the following question: if science relies heavily on induction, does philosophy of science rely heavily on induction as well? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database (n = 14,199) in order to answer this question empirically. If philosophy of science relies heavily on induction, just as science supposedly does, then we would expect to find significantly more inductive arguments than (...) deductive arguments and abductive arguments in the published works of philosophers of science. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we search through our corpus to find patterns of argumentation. Overall, the results of our study suggest that philosophers of science do rely on inductive inference. But induction may not be as foundational to philosophy of science as it is thought to be for science, given that philosophers of science make significantly more deductive arguments than inductive arguments. Interestingly, our results also suggest that philosophers of science do not rely on abductive arguments all that much, even though philosophers of science consider abduction to be a cornerstone of scientific methodology. (shrink)

We present a reference model for finding evidence of discrimination in datasets of historical decision records in socially sensitive tasks, including access to credit, mortgage, insurance, labor market and other benefits. We formalize the process of direct and indirect discrimination discovery in a rule-based framework, by modelling protected-by-law groups, such as minorities or disadvantaged segments, and contexts where discrimination occurs. Classification rules, extracted from the historical records, allow for unveiling contexts of unlawful discrimination, where the degree of burden over protected-by-law (...) groups is evaluated by formalizing existing norms and regulations in terms of quantitative measures. The measures are defined as functions of the contingency table of a classification rule, and their statistical significance is assessed, relying on a large body of statistical inference methods for proportions. Key legal concepts and reasonings are then used to drive the analysis on the set of classification rules, with the aim of discovering patterns of discrimination, either direct or indirect. Analyses of affirmative action, favoritism and argumentation against discrimination allegations are also modelled in the proposed framework. Finally, we present an implementation, called LP2DD, of the overall reference model that integrates induction, through data mining classification rule extraction, and deduction, through a computational logic implementation of the analytical tools. The LP2DD system is put at work on the analysis of a dataset of credit decision records. (shrink)

This paper focuses on abduction as explicit or readily formulatable inference to possible explanatory hypotheses--as contrasted with inference to conceptual innovations or abductive logic as a cycle of hypotheses, deduction of consequences and inductive testing. Inference to an explanation is often a matter of projection or extrapolation of elements of accepted theory for the solution of outstanding problems in particular domains of inquiry. I say "projections or extrapolation" of accepted theory, but I mean to point to something broader and (...) suggest how elements of accepted theory constrain emergent models and plausible inferences to explanations--in a quasi-rationalist fashion. I draw on illustrations from quantum gravity below just because there is so little direct evidence available in the field. It is in such cases that Peirce's discussions of abductive inference provide the most plausible support for the idea of a logic of abduction--as inference to readily formulatable explanatory hypotheses. The possible need for conceptual innovation points to the limits on the possibility of a logic of abduction of a more rationalistic character--selecting uniquely superior explanations. Abduction conceived as a repeated cycle of inquiry also points to limits on our expectations for an abductive logic. My chief point is that the character of inference to an explanation, viewed below as embedded within arguments from analogy, is so little compelling, as a matter of logical form alone, that there will always be a pluralism of plausible alternatives among untested hypotheses and inferences to them--calling for some comparative evaluation. This point leads on to some consideration of the virtues of hypotheses--as a description of the range of this pluralism. (shrink)

Drawing on Charles Peirce’s descriptions of his correspondence course on the “Art of Reasoning,” I argue that Peirce believed that the study of logic stands at the center of a liberal arts education. However, Peirce’s notion of logic included much more than the traditional accounts of deduction and syllogistic reasoning. He believed that the art of reasoning required a study of both abductive and inductive inference as well the practice of observation and imagination. Employing these other (...) features of logic, his course foreshadowed a number of developments in twentieth century educational theory: the belief that non-traditional students should be educated, the claim that the art of reasoning was important to all theoretical practices, and that the art of reasoning was important to the overall growth of a person. The upshot is that Peirce’s course in the art of reasoning should make us reconsider making logic courses, under Peirce’s broad conception of logic, required courses in high school and higher education. (shrink)

Abduction* is the genus with deduction and induction as species. Modus tollens is backward reasoning as an unknown proposition is inferred from a known proposition. Reductio ad absurdum is abductive because the conclusion is inferred by deriving a contradiction from an assumption. Inductive reasoning from effect to cause is also backward reasoning. But abduction* consists of forward reasoning as well. The generic structure of abductive* argumentation is universal among all cultures, occupations and disciplines.

The paper aims to expose the induction – deduction relation within W. Whewell’s treatise «Novum Organon Renovatum». Since Aristotle’s time. induction and deduction have been interpreted as independent and even «opposite» inferences (ways of connecting premises and conclusions), but this intuition is violated in W. Whewell’s works. Based on contemporary practice of some specific natural sciences W. Whewell quite reasonably concludes that “Aristotle overlooks a step which is of far more importance to our knowledge, namely, the invention of the second (...) extreme term” and that “induction moves upward, and deduction downwards the same stair”. Ultimately, assessing the contribution of W. Whewell to the development and consolidation of the classical image of science, it can be noted that his thesis that “deduction justifies induction” is much more in line with the instrumentalism of E. Mach and A. Poincaré than J. Mill’s inductivism. (shrink)

This is an excerpt from the contentMost academics have heard of deduction and induction, but much less familiar is the kind of inference that the American philosopher Charles Peirce called abduction. Abductive inference is the generation and evaluation of explanatory hypotheses, a kind of reasoning that is far more common and important than deductions, which rarely occur outside of mathematics, and inductions from examples to generalizations. Lorenzo Magnani has produced a magnum opus on abduction that brilliantly spans its (...) philosophical, neuropsychological, computational, and ecological dimensions. In this review I will briefly highlight some of the substantial contributions of Abductive Cognition and raise a few objections to it. I finish by briefly discussing the relevance of abduction to concerns about mind and society. Magnani’s treatise is by far the most comprehensive discussion of abductive thinking to date. In the first chapter, he reviews various ways of thinking about abduction, ranging from sentential approac. (shrink)

This paper introduces an epistemological model of scientific reasoning which can be described in terms of abduction, deduction and induction. The aim is to emphasize the significance of abduction in order to illustrate the problem-solving process and to propose a unified epistemological model of scientific discovery. The model first describes the different meanings of the word abduction in order to clarify their significance for epistemology and artificial intelligence. In different theoretical changes in theoretical systems we witness different kinds of (...) discovery processes operating. Discovery methods are "data-driven," "explanation-driven", and "coherence-driven". Sometimes there is a mixture of such methods: for example, an hypothesis devoted to overcome a contradiction is found by abduction. Contradiction, far from damaging a system, help to indicate regions in which it can be changed and improved. I will also consider a kind of "weak" hypothesis that is hard to negate and the ways for making it easy. In these cases the subject can "rationally" decide to withdraw his or her hypotheses even in contexts where it is "impossible" to find "explicit" contradictions and anomalies. Here, the use of negation as failure is illuminating. (shrink)

Here the author of How to Solve It explains how to become a "good guesser." Marked by G. Polya's simple, energetic prose and use of clever examples from a wide range of human activities, this two-volume work explores techniques of guessing, inductive reasoning, and reasoning by analogy, and the role they play in the most rigorous of deductive disciplines.

The study of deductive reasoning has been a major paradigm in psychology for approximately the past 40 years. Research has shown that people make many logical errors on such tasks and are strongly influenced by problem content and context. It is argued that this paradigm was developed in a context of logicist thinking that is now outmoded. Few reasoning researchers still believe that logic is an appropriate normative system for most human reasoning, let alone a model for (...) describing the process of human reasoning, and many use the paradigm principally to study pragmatic and probabilistic processes. It is suggested that the methods used for studying reasoning be reviewed, especially the instructional context, which necessarily defines pragmatic influences as biases. (shrink)

While Kant does not address the problem of induction often attributed to Hume, he does, by way of a transcendental deduction of an a priori principle of reflecting empirical judgment, address a distinct problem Hume raises indirectly. This problem is that induction cannot be justified so long as it presupposes some empirical concept applying to or some empirical principle true of more than one object in nature, a presupposition neither determined by nor founded on reason. I draw on Hume’s positive (...) account of induction to motivate the following objection to Kant: in so far as induction can be justified, there is reason to doubt that it would be so in virtue of any a priori feature. (shrink)

How do you tell what’s right from what’s wrong? Can you always? What’s the difference between deduction, induction, and abduction? What are the best techniques for making an argument logically sound? In this fascinating little book, the smallest on its subject ever produced, philosopher Earl Fontainelle explores the ancient art of discursive Logic and demonstrates some of the techniques that have long been used to triumph over the debates and deceptions that assail us every day. Filled with helpful examples of (...) good and bad reasoning, Logic is an invaluable introduction to a defining human characteristic. (shrink)

Debates concerning the character, scope, and warrant of abductive inference have been active since Peirce first proposed that there was a third form of inference, distinct from induction and deduction. Abductive reasoning has been dubbed weak, incoherent, and even nonexistent. Part, at least, of the problem of articulating a clear sense of abductive inference is due to difficulty in interpreting Peirce. Part of the fault must lie with his critics, however. While this article will argue that (...) Peirce indeed left a number of puzzles for interpreters, it will also contend that interpreters should be careful to distinguish discussion of the formal and strictly epistemic question of whether and how abduction is a sound form of inference from discussions of the practical goals of abduction, as Peirce understood them. This article will trace a history of critics and defenders of Peirce’s notion of abduction and discuss how Peirce both fueled the confusion and in fact anticipated and responded to several recurring objections. (shrink)

Charles S. Peirce’s conception of abductive reasoning became a hot topic in the philosophy of science after World War II, when N. R. Hanson suggested that abduction is a logic of discovery, Gilbert Harman argued that all types of inductive reasoning can be reduced to inference to the best explanation, and Howard Smokler suggested that abduction as inverse deduction is an important method of confirmation. Abduction has been a popular theme also in Artificial Intelligence. Illustrations and examples (...) of abduction have been sought in everyday life, detective stories, and many scientific disciplines from astronomy to medicine. Iddo Tavory and Stefan Timmermans have published a book on qualitative... (shrink)

Epistemologists and philosophers of science have often attempted to express formally the impact of a piece of evidence on the credibility of a hypothesis. In this paper we will focus on the Bayesian approach to evidential support. We will propose a new formal treatment of the notion of degree of confirmation and we will argue that it overcomes some limitations of the currently available approaches on two grounds: (i) a theoretical analysis of the confirmation relation seen as an extension of (...) logical deduction and (ii) an empirical comparison of competing measures in an experimental inquiry concerning inductive reasoning in a probabilistic setting. (shrink)