This book examines the philosophical conception of abductive reasoning as developed by Charles S. Peirce, the founder of American pragmatism. It explores the historical and systematic connections of Peirce's original ideas and debates about their interpretations. Abduction is understood in a broad sense which covers the discovery and pursuit of hypotheses and inference to the best explanation. The analysis presents fresh insights into this notion of reasoning, which derives from effects to causes or from surprising observations to explanatory theories. The (...) author outlines some logical and AI approaches to abduction as well as studies various kinds of inverse problems in astronomy, physics, medicine, biology, and human sciences to provide examples of retroductions and abductions. The discussion covers also everyday examples with the implication of this notion in detective stories, one of Peirce’s own favorite themes. The author uses Bayesian probabilities to argue that explanatory abduction is a method of confirmation. He uses his own account of truth approximation to reformulate abduction as inference which leads to the truthlikeness of its conclusion. This allows a powerful abductive defense of scientific realism. This up-to-date survey and defense of the Peircean view of abduction may very well help researchers, students, and philosophers better understand the logic of truth-seeking. (shrink)

We present preliminary results on modelling structure of solutions to a task involving abductive reasoning. Research data were gathered using our new tool—Find Out, which has been designed in order to account empirically for abduction relatively close to everyday reasoning processes, with the necessary level of procedure standardization. The tool enables to capture abduction as a compound form of reasoning, from both product and process perspective. Find Out is set up as a game that requires playing the role of an (...) investigator seeking an explanation of what has happened in the presented enigmatic situation. The task consists of three time-limited stages that require different reasoning activities. In the paper, we present quantitative models of structures of solutions to the task proposed by the subjects in the form of situational graphs. We present also some ideas concerning qualitative characteristics of these solutions. (shrink)

When someone is asked to speak his mind, it is sometimes possible for him to furnish what his utterance appears to have omitted. In such cases we might say that he had a mind to speak. Sometimes, however, the opposite is true. Asked to speak his mind, our speaker finds that he has no mind to speak. When it is possible to speak one's mind and when not is largely determined by the kinds of beings we are and by the (...) kinds of resources we are able to draw upon. In either case, not speaking one's mind is leaving something out whose articulation would or could matter for the purposes for which one was speaking in the first place. Inarticulation is no fleetingly contingent and peripheral phenomenon in human thinking and discourse. It is a substantial and dominant commonplace. In Part One I attempt to say something about what it is about the human agent that makes inarticulateness so rife. In Part Two, I consider various strategies for making the unarticulated explicit, and certain constraints on such processes. I shall suggest, among other things, that standard treatments of enthymematic reconstruction are fundamentally misconceived. (shrink)

The purpose of this work is to analyse the cognitive process of the domain theories in terms of the measurement theory to develop a computational machine learning approach for implementing it. As a result, the relational data mining approach, the authors proposed in the preceding books, was improved. We present the approach as an implementation of the cognitive process as the measurement theory perceived. We analyse the cognitive process in the first part of the paper and present the theory and (...) method of the logically most powerful empirical theory discovery in the second. The theory is based on the notion of law-like rules, which conform to all the properties of laws of nature, namely generality, simplicity, maximum refutability and minimum number of parameters. This notion is defined for deterministic and probabilistic cases. Based on the method, the discovery system is developed. The system was successfully applied to many practical tasks. (shrink)

The concept of preadaptation, though useful, continues to trouble evolutionary scientists. Usually, it is treated as if it were really adaptation, prompting such diverse theorists as Gould and Vrba, and Dennett to suggest its removal from evolutionary theory altogether. In this paper, I argue that the as-if sense is ill-founded, and that the sense of preadaptation as a process may be defended as unequivocal and generally useful in evolutionary explanations, even in such problem areas as human evolution.

Many cognitive scientists, having discovered that some computational-level characterization f of a cognitive capacity φ is intractable, invoke heuristics as algorithmic-level explanations of how cognizers compute f. We argue that such explanations are actually dysfunctional, and rebut five possible objections. We then propose computational-level theory revision as a principled and workable alternative.

This article analyzes three approaches to resolving the classical Meno paradox, or its variant, the learning paradox, emphasizing Charles S. Peirce’s notion of abduction. Abduction provides a way of dissecting those processes where something new, or conceptually more complex than before, is discovered or learned. In its basic form, abduction is a “weak” form of inference, i.e., it gives only tentative suggestions for further investigation. But it is not too weak if various sources of clues and restrictions on the abductive (...) search are taken into account. We present three, complementary versions of abduction: as a sort of guessing instinct or expert-like intuition, where unconscious clues are important; as a form of inference, where a strategic point of view is essential; and as a part of distributed cognition and mediated activity, where the interaction with the material, social, and cultural environment is emphasized. Our starting point is Peirce’s own notion of abduction, but we broaden the perspective, especially to the direction of distributed cognition. (shrink)

There are various ``classical'' arguments against abduction as a logic of discovery,especially that (1) abduction is too weak a mode of inference to be of any use, and (2) in basic formulation of abduction the hypothesisis already presupposed to be known, so it is not the way hypotheses are discovered in the first place. In this paper I argue, by bringing forth the idea of strategies,that these counter-arguments are weaker than may appear. The concept of strategies suggests, inter alia, that (...) many inferential moves are taken into account at the same time. This is especially important in abductive reasoning, which is basically a very weak mode of inference. The importance of strategic thinking can already be seen in Charles S.Peirce's early treatments of the topic, and N.R.Hanson's later writings on abduction although they did not use the concept of``strategies.'' On the whole, I am arguing that the focus should be more on methodological processes, and not only on validity considerations, which have dominated the discussion about abduction. (shrink)

Prezentujemy dwa formalne narzędzia służące do modelowania rozumowań, za pomocą których rozwiązywane są szczególnego rodzaju problemy abdukcyjne. Pierwszy model, osadzony w formalizmie logiki pytań, bazuje na pojęciu słabej implikacji erotetycznej. Drugi model wykorzystuje relacje zawężania i odsiewania definiowane za po-mocą logiki pytań, semantyki sytuacyjnej i pojęcia relewancjiwątku. Na przykładzie analizy rozgrywek w grę Takie Życie pokazujemy, że oba modele adekwatnie charakteryzują dane empiryczne.

Our brains make up a series of signs and are engaged in making or manifesting or reacting to a series of signs: through this semiotic activity they are at the same time engaged in “being minds” and so in thinking intelligently. An important effect of this semiotic activity of brains is a continuous process of “externalization of the mind” that exhibits a new cognitive perspective on the mechanisms underling the semiotic emergence of abductive processes of meaning formation. To illustrate this (...) process I will take advantage of the analysis of some aspects of the cognitive interplay between internal and external representations. I consider this interplay critical in analyzing the relation between meaningful semiotic internal resources and devices and their dynamical interactions with the externalized semiotic materiality suitably stocked in the environment. Hence, minds are material, “extended” and artificial in themselves. A considerable part of human abductive thinking is occurring through an activity consisting in a kind of reification in the external environment and a subsequent re-projection and reinterpretation through new configurations of neural networks and chemical processes. I also illustrate how this activity takes advantage of hybrid representations and how it can nicely account for various processes of creative and selective abduction, bringing up the question of how multimodal aspects involving a full range of sensory modalities are important in hypothetical reasoning. (shrink)

Computational philosophy (CP) aims at investigating many important concepts and problems of the philosophical and epistemological tradition in a new way by taking advantage of information-theoretic, cognitive, and artificial intelligence methodologies. I maintain that the results of computational philosophy meet the classical requirements of some Peircian pragmatic ambitions. Indeed, more than a 100 years ago, the American philosopher C.S. Peirce, when working on logical and philosophical problems, suggested the concept of pragmatism(pragmaticism, in his own words) as a logical criterion to (...) analyze what words and concepts express through their practical meaning. Many words have been spent on creative processes and reasoning, especially in the case of scientific practices. In fact, many philosophers have usually offered a number of ways of construing hypotheses generation, but they aim at demonstrating that the activity of generating hypotheses is paradoxical, obscure, and thus not analyzable. Those descriptions are often so far from Peircian pragmatic prescription and so abstract to result completely unknowable and obscure. To dismiss this tendency and gain interesting insight about the so-called logic of scientific discovery we need to build constructive procedures, which could play a role in moving the problem-solving process forward by implementing them in some actual models. The computational turn gives us a new way to understand creative processes in a strictly pragmatic sense. In fact, by exploiting artificial intelligence and cognitive science tools, computational philosophy allows us to test concepts and ideas previously conceived only in abstract terms. It is in the perspective of these actual computational models that I find the central role of abduction in the explanation of creative reasoning in science. I maintain that the computational philosophy analysis of model-based and manipulative abduction and of external and epistemic mediators is important not only to delineate the actual practice of abduction, but also to further enhance the development of programs computationally adequate in rediscovering, or discovering for the first time, for example, scientific hypotheses or mathematical theorems. The last part of the paper is devoted to illustrating the problem of the extra-theoretical dimension of reasoning and discovery from the perspective of some mathematical cases derived from calculus and geometry. (shrink)

More than a hundred years ago, the American philosopher C. S. Peirce suggested the idea of pragmatism as a logical criterion to analyze what words and concepts express through their practical meaning. Many words have been spent on creative processes and reasoning, especially in the case of scientific practices. In fact, philosophers have usually offered a number of ways of construing hypotheses generation, but all aim at demonstrating that the activity of generating hypotheses is paradoxical, illusory or obscure, and thus (...) not analyzable. The “computational turn” gave us a new way to understand creative processes in a strictly pragmatic sense. Artificial Intelligence and Cognitive Science tools allow us to test concepts and ideas previously conceived in abstract terms. It is in the perspective of these actual models that we find the central role of abduction in the explanation of creative reasoning in science. What I call theoretical abduction certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good explanations of data, but fails to account for many cases of explanation occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I call epistemic mediators, which are illustrated in the last part of the paper. (shrink)

Although the importance of measuring and reporting the social and environmental impact of organisational action is increasingly well recognised by both organisations and society at large, existing approaches to impact measurement are still far from being universally accepted. In this context, the stakeholder dynamics within the nascent field of impact investing demonstrate the complexity of resolving potentially differing perspectives on key impact measurement issues such as materiality. This paper argues, from an organisational perspective, that such arenas of contestation can be (...) conceptualised in terms of social justice. Specifically, we draw upon Sen’s notions of ‘arrangement and realisation’ to explore the dynamics of contestation across a range of stakeholders concerning materiality judgements to suggest that such ‘arrangements’ may lead to suboptimal impact outcomes as ‘realisations.’ Our analysis of the nature of materiality contestations in impact measurement reveals the conflicts, tensions and paradoxes evident in this field of action. Empirically, we examine data drawn from 19 cases and 33 interviews. The analysis suggests three arenas of contestation around the materiality of impact measurement: the power dynamics between economically powerful investors and objectified investees; the conflicts between materiality norms and standards; and the interactions between all stakeholders with differing motivations towards radical or incremental materiality. Building upon this analysis, we then discuss how arenas of contested materiality may be mediated by drawing upon Sen’s notions of transcending the individual interests of the invested parties for the greater good via processes of contextualisation and case-specificity. (shrink)

IntroductionIf we were to identify the beginning of the study of visual argumentation, we would have to choose 1996 as the starting point. This was the year that Leo Groarke published “Logic, art and argument” in Informal logic, and it was the year that he and David Birdsell co-edited a special double issue of Argumentation and Advocacy on visual argumentation . Among other papers, the issue included Anthony Blair’s “The possibility and actuality of visual arguments”. It was also the year (...) that Gail J. Chryslee, Sonja K. Foss and Arthur L. Ranney published their short text on “The construction of claims in visual argumentation” , stating that even though theorists may know a great deal about the process of argumentation, “virtually none of this knowledge is applicable to visual argumentation […] because of the properties that distinguish visual imagery from discursive symbols” .Texts on visual rhetoric have been written as far back as the early 1980s, .. (shrink)

This paper defines in a formal and computational way the notion of ‘consilience’, a term introduced by Whewell in 1847 for the evaluation of scientific theories. Informally, as has been used to date, a model or theory is ‘consilient’ if it is predictive, explanatory and unifies the evide-nce. Centred in a constructive framework, where new terms can be intro-duced, we essay a formalisation of the idea of unification based on the avoidance of ‘sepa-ration’. However, it is soon manifest that this (...) classical approach is vulnerable to the introduction of fantastic concepts to unify disparate sub-theories. Our second approach is constructed by using a detailed evaluation of the relationship between the theory and the evid-ence by means of reinforcement propagation. With the use of reinfor-cement, fantastic concepts can be better detected and the role of con-silience for theory construction and revision can be specialised for dif-ferent inference mechanisms like explanatory induction, abduction, deduc-tion and analogy. (shrink)

This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one story-based. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of (...) an event, e.g., based on witness testimony, are central. In a story-based approach, evidence is evaluated and interpreted from the perspective of the factual stories as they may have occurred in a case, e.g., as they are defended by the prosecution. In this paper, we argue that both arguments and narratives are relevant and useful in the reasoning with and interpretation of evidence. Therefore, a hybrid approach is proposed and formally developed, doing justice to both the argument-based and the narrative-based perspective. By the formalization of the theory and the associated graphical representations, our proposal is the basis for the design of software developed as a tool to make sense of the evidence in complex cases. (shrink)

Delusional beliefs have sometimes been considered as rational inferences from abnormal experiences. We explore this idea in more detail, making the following points. Firstly, the abnormalities of cognition which initially prompt the entertaining of a delusional belief are not always conscious and since we prefer to restrict the term “experience” to consciousness we refer to “abnormal data” rather than “abnormal experience”. Secondly, we argue that in relation to many delusions (we consider eight) one can clearly identify what the abnormal cognitive (...) data are which prompted the delusion and what the neuropsychological impairment is which is responsible for the occurrence of these data; but one can equally clearly point to cases where this impairments is present but delusion is not. So the impairment is not sufficient for delusion to occur. A second cognitive impairment, one which impairs the ability to evaluate beliefs, must also be present. Thirdly (and this is the main thrust of our chapter) we consider in detail what the nature of the inference is that leads from the abnormal data to the belief. This is not deductive inference and it is not inference by enumerative induction; it is abductive inference. We offer a Bayesian account of abductive inference and apply it to the explanation of delusional belief. (shrink)

Here are some of the most important discoveries in the history of medicine: blood circulation (1620s), vaccination, (1790s), anesthesia (1840s), germ theory (1860s), X- rays (1895), vitamins (early 1900s), antibiotics (1920s-1930s), insulin (1920s), and oncogenes (1970s). This list is highly varied, as it includes basic medical knowledge such has Harvey’s account of how the heart pumps blood, hypotheses about the causes of disease such as the germ theory, ideas about the treatments of diseases such as antibiotics, and medical instruments such (...) as X-ray machines. The philosophy of medicine should be able to contribute to understanding of the nature of discoveries such as these. The great originators of the field of philosophy of science were all concerned with the nature of scientific discovery, including Francis Bacon (1960), William Whewell (1967), John Stuart Mill (1974), and Charles Peirce (1931-1958). The rise of logical positivism in the 1930s pushed discovery off the philosophical agenda, but the topic was revived through the work of philosophers such as Norwood Russell Hanson (1958), Thomas Nickles (1980), Lindley Darden (1991, 2006), and Nancy Nersessian (1984). Scientific discovery has also become an object of investigations for researchers in the fields of cognitive psychology and artificial intelligence, as seen in the work of Herbert Simon, Pat Langley, and others (Langley et al., 1987; Klahr, 2000). Today, scientific September 14, 2009 discovery is an interdisciplinary topic at the intersection of the philosophy, history, and psychology of science. The aim of this chapter is to identify patterns of discovery that illuminate some of the most important developments in the history of medicine. I have used a variety of sources to identify forty great medical discoveries (Adler, 2004; Friedman and Friedland, 1998; Science Channel, 2006; Strauss and Strauss, 2006).. (shrink)