Inspired by Bermúdez’s notion of proto-logic, I would like to fathom what the true proto-logic could be like. But this will be approached only in a negative way of figuring out what it could not be. I shall argue that it could not be purely deductive by exploiting the recent researches in logic of maps. This will allow us to reorient the search for proto-logic, starting with animal abduction. I will also suggest that proto-logic won’t get off the ground without (...) proto-geometry. These negative results will shed some lights on some further conceptual and historical issues around the language of thought hypothesis to arrive at the true proto-logic. (shrink)

Currently, there is a focus in science education on preparing students for lives as innovative and resilient citizens of the twenty-first century. Key to this is providing students with opportunities, mainly through inquiry processes, for discovery making and developing their creative reasoning by bringing school science closer to authentic science. I propose, building on the work of Woods, Magnani and the authors of a 2005 special issue of Educational Philosophy and Theory on Peirce, that these efforts can be advanced through (...) the adoption of a Peircean logic of discovery in the science classroom. I further suggest that this can only take place if a classical logic that frames school science, which deems abduction—the creative element of reasoning that drives discovery—as fallacious and not valuable as an inference making process, is replaced with a naturalised logic. Such a logic positions students as practical, not ideal agents of reasoning who in their hypothesis making are inferential-experts... (shrink)

Abductive problems and their solutions are presented by means of justification logic. We introduce additional meta-constructions in order to generate and compare different solutions to the same abductive problem. Our approach has three advantages: (i) it makes structurally explicit the solution to an abductive problem (as it has a syntactic nature); (ii) it gives a precise meaning to the notion of evidence; (iii) it provides clear definitions and procedures for the comparison of solutions that can be adapted to different needs.

In this paper we seek an inferential and cognitive model explaining some characteristics of abduction to composite hypotheses. In the first section, we introduce the matter of composite hypotheses, stressing how it is coherent with the intuitive and philosophical contention that a single event can be caused not only by several causes acting together, but also by several kinds of causation. In the second section, we argue that gossip could serve as an interesting model to study the generation of composite (...) hypotheses at a larger scale: several characteristics of gossip make it extremely prone to produce composite hypotheses considering different levels of causation. In the third and final section, we try to illustrate some specificities of abduction to composite hypotheses for individual agents basing on the analysis of collective agents. (shrink)

The aim of this article is to analyse the kind of inference used in the reconstruction of proto-languages. Hypothesis is at the core of this reconstruction process and this, together with the structure of reasoning involved, indicates abductive reasoning. We analyse abductive reasoning, and specify its nuances and particularities. The novelty we introduce is the importance of context as we focus on a form of abduction that goes beyond the context in which the scientific work is being developed by incorporating (...) contexts from other sciences. Therefore, an intercontextual chain of inference can be part of abductive reasoning processes and the resulting hypothesis remains provisional. Several disciplines, such as archaeology, history and linguistics, play a cognitive role in the reconstruction of proto-languages, thus requiring more than one context. We use the case of the reconstruction of proto-Semitic and the unexpected fact of the Ugarit and Ebla discoveries (plus Amorite names). This sample may shed light on the use of abduction to explain certain scientific practices. (shrink)

Abduction is considered the most powerful, but also the most controversially discussed type of inference. Based on an analysis of Peirce’s retroduction, Lipton’s Inference to the Best Explanation and other theories, a new theory of abduction is proposed. It considers abduction not as intrinsically explanatory but as intrinsically conditional: for a given fact, abduction allows one to infer a fact that implies it. There are three types of abduction: Selective abduction selects an already known conditional whose consequent is the given (...) fact and infers that its antecedent is true. Conditional-creative abduction creates a new conditional in which the given fact is the consequent and a defined fact is the antecedent that implies the given fact. Propositional-conditional-creative abduction assumes that the given fact is implied by a hitherto undefined fact and thus creates a new conditional with a new proposition as antecedent. The execution of abductive inferences is specified by theory-specific patterns. Each pattern consists of a set of rules for both generating and justifying abductive conclusions and covers the complete inference process. Consequently, abductive inferences can be formalised iff the whole pattern can be formalised. The empirical consistency of the proposed theory is demonstrated by a case study of Semmelweis' research on puerperal fever. (shrink)

In my opinion, it is only in the framework of a research dealing with abductive cognition that we can analyze important cognitive aspects of human and machine capacities. From the point of view of human capacities the phenomenological concept of anticipation, which is related to the problem of the spontaneous generation of spatiality and its three-dimensionality, will be central. I will describe that anticipations can be seen as types of visual and manipulative abduction and also fruitful to illustrate, in the (...) case of human and machine capacities, the respective role of two kinds of strategic reasoning: locked and unlocked abductive strategies, which characterize the basic cognitive pro- cedure of “reading ahead”. The specificity of these contrasting inferential strategies is also related to their potentiality in producing different kinds of hypothetical outcomes, which in turn represent dissimilar levels of knowledge creativity. This diversity is also fundamental to depict the special character, the kind of creativity, and the limits of current computational deep learning AI systems, such as AlphaGo, which realize abductive cognitive processes. (shrink)

During the second half of the last century, the importance of serendipitous events in scientific frameworks has been progressively recognized, fueling hard debates about their role, nature, and structure in philosophy and sociology of science. Alas, while discussing the relevance of the topic for the comprehension of the nature of scientific discovery, the philosophical literature has hardly paid attention to the cognitive significance of serendipity, accepting rather than examining some of its most specific features, such as its game-changing effect, the (...) unexpectedness of its occurrence, and its affinity with the concept of “luck”. Thus, in this paper we aim at analyzing these characteristics in the light of their cognitive implications in the recognition, performance, and possible stimulation of serendipitous events in relation to scientific discoveries. (shrink)

_Locked_ and _unlocked_ strategies are illustrated in this article as concepts that deal with important cognitive aspects of deep learning systems. They indicate different inference routines that refer to poor (locked) to rich (unlocked) cases of creative production of creative cognition. I maintain that these differences lead to important consequences when we analyze computational deep learning programs, such as AlphaGo/AlphaZero, which are able to realize various types of abductive hypothetical reasoning. These programs embed what I call locked abductive strategies, so, (...) even if they present spectacular performances for example in games, they are characterized by poor types of hypothetical creative cognition insofar as they are constrained in what I call _eco-cognitive openness_. This openness instead characterizes unlocked human cognition that pertains to higher kinds of abductive reasoning, in both the creative and diagnostic cases, in which cognitive strategies are instead unlocked. This special kind of “openness” is physically rooted in the fundamental character of the human brain as an open system constantly coupled with the environment (that is, an “open” or “dissipative” system): its activity is the uninterrupted attempt to achieve the equilibrium with the environment in which it is embedded, and this interplay can never be switched off without producing severe damage to the brain. The brain cannot be conceived as deprived of its physical quintessence that is its openness. In the brain, contrary to the computational case, ordering is not derived from the outside thanks to what I have called in a recent book “computational domestication of ignorant entities”, but it is the direct product of an “internal” open dynamical process of the system. (shrink)

This book employs a new eco-cognitive model of abduction to underline the distributed and embodied nature of scientific cognition. Its main focus is on the knowledge-enhancing virtues of abduction and on the productive role of scientific models. What are the distinctive features that define the kind of knowledge produced by science? To provide an answer to this question, the book first addresses the ideas of Aristotle, who stressed the essential inferential and distributed role of external cognitive tools and epistemic mediators (...) in abductive cognition. This is analyzed in depth from both a naturalized logic and an ecology of cognition perspective. It is shown how the maximization of cognition, and of abducibility – two typical goals of science – are related to a number of fundamental aspects: the optimization of the eco-cognitive situatedness; the maximization of changeability for both the input and the output of the inferences involved; a high degree of information-sensitiveness; and the need to record the “past life” of abductive inferential practices. Lastly, the book explains how some impoverished epistemological niches – the result of a growing epistemic irresponsibility associated with the commodification and commercialization of science – are now seriously jeopardizing the flourishing development of human creative abduction. (shrink)

In this paper, we aim at explaining the relevance of thought experiments in philosophy and the history of science by describing them as particular instances of two categories of creative thinking: metaphorical reasoning and abductive cognition. As a result of this definition, we will claim that TEs hold an ignorance-preserving trait that is evidenced in both TEs inferential structure and in the process of scenario creation they presuppose. Elaborating this thesis will allow us to explain the wonder that philosophers of (...) science have consistently shown for TEs, as well as the high functionality of TEs in the creative aspects of scientific and philosophical praxis. (shrink)

Peirce made repeated attempts to clarify what he understood as abduction or creative reasoning in scientific discoveries. In this article, we draw on past and recent scholarship on Peirce’s later accounts of abduction to put a case for how teachers can apply his ideas productively to elicit and guide student creative reasoning in the science classroom. We focus on (a) his rationale for abduction, (b) conditions he recognised as necessary to support this speculative reasoning, (c) pragmatic strategies to guide inquiry (...) and test conjectural hypotheses, and (d) his growing recognition of creative dimensions to reasoning beyond abductive inference-making. We illustrate this case through examples of a guided inquiry approach to student claim-making in the science classroom. (shrink)

Cognitive niche construction theory provides a new comprehensive account for the development of human cultural and social organization with respect to the management of their environment. Cognitive niche construction can be seen as a way of lessening complexity and unpredictability of a given environment. In this paper, we are going to analyze economic systems as highly technological cognitive niches, and individuate a link between cognitive niche construction, unpredictability and a particular kind of economic crises.

I will analyse some properties of abduction that are essential from a logical standpoint. When dealing with the so-called ‘inferential problem’, I will opt for the more general concepts of input and output instead of those of premisses and conclusions, and show that in this framework two consequences can be derived that help clarify basic logical aspects of abductive reasoning: (i) it is more natural to accept the ‘multimodal’ and ‘context-dependent’ character of the inferences involved, (ii) inferences are not merely (...) conceived of in the terms of the process leading to the ‘generation of an output’ or to the proof of it, as in the traditional and standard view of deductive proofs, but rather, from this perspective abductive inferences can be seen as related to logical processes in which input and output fail to hold each other in an expected relation, with the solution involving the modification of inputs, not that of outputs. I will also describe that if we wish to naturalize the logic of the abductive processes and its special consequence relation, we should refer to the following main aspects: ‘optimization of situatedness’, ‘maximization of changeability’ of both input and output, and high ‘information-sensitiveness’. (shrink)

Locked and unlocked strategies are at the center of this article, as ways of shedding new light on the cognitive aspects of deep learning machines. The character and the role of these cognitive strategies, which are occurring both in humans and in computational machines, is indeed strictly related to the generation of cognitive outputs, which range from weak to strong level of knowledge creativity. I maintain that these differences lead to important consequences when we analyze computational AI programs, such as (...) AlphaGo, which aim at performing various kinds of abductive hypothetical reasoning. In these cases, the programs are characterized by _locked_ abductive strategies: they deal with weak (even if sometimes amazing) kinds of hypothetical creative reasoning, because they are limited in what I call eco-cognitive openness, which instead qualifies human cognizers who are performing higher kinds of abductive creative reasoning, where cognitive strategies are instead _unlocked_. (shrink)