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.

This book ties together the concerns of philosophers of science and AI researchers, showing for example the connections between scientific thinking and medical expert systems. It lays out a useful general framework for discussion of a variety of kinds of abduction. It develops important ideas about aspects of abductive reasoning that have been relatively neglected in cognitive science, including the use of visual and temporal representations and the role of abduction in the withdrawal of hypotheses.

This book contains contributions presented during the international conference on Model-Based Reasoning (MBR ́012), held on June 21-23 in Sestri Levante, Italy. Interdisciplinary researchers discuss in this volume how scientific cognition and other kinds of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. Some of the contributions analyzed the problem of model-based reasoning in technology and stressed the issues of scientific and technological innovation. The book is divided in three main parts: models, mental models, representations; abduction, problem solving and practical reasoning; historical, epistemological and technological issues. The volume is based on the papers that were presented at the international

The volume is based on the papers that were presented at the Interna tional Conference Model-Based Reasoning in Scientific Discovery (MBR'98), held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 1998. The papers explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The study of diagnostic, visual, spatial, analogical, and temporal rea soning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of tradi tional notions of reasoning such as classical logic. Traditional accounts of scientific reasoning have restricted the notion of reasoning primarily to de ductive and inductive arguments. Understanding the contribution of model ing practices to discovery and conceptual change in science requires ex panding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philoso phy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model based reasoning to be considered in this book. The models are intended as in terpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain.

There are several key ingredients common to the various forms of model-based reasoning considered in this book. The term ‘model’ comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations and are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. The book’s contributors are researchers active in the area of creative reasoning in science and technology.

This volume sets out to give a philosophical “applied” account of violence, engaged with both empirical and theoretical debates in other disciplines such as cognitive science, sociology, psychiatry, anthropology, political theory, evolutionary biology, and theology. The book’s primary thesis is that violence is inescapably intertwined with morality and typically enacted for “moral” reasons. To show this, the book compellingly demonstrates how morality operates to trigger and justify violence and how people, in their violent behaviors, can engage and disengage with discrete moralities. The author’s fundamental account of language, and in particular its normative aspects, is particularly insightful as regards extending the range of what is to be understood as violence beyond the domain of physical harm. By employing concepts such as “coalition enforcement”, “moral bubbles”, “cognitive niches”, “overmoralization”, “military intelligence” and so on, the book aims to spell out how perpetrators and victims of violence systematically disagree about the very nature of violence. The author’s original claim is that disagreement can be understood naturalistically, described by an account of morality informed by evolutionary perspectives as well. This book might help us come to terms with the fact that we are intrinsically “violent beings”. To acknowledge this condition, and our stupefying capacity to inflict harm, is a responsibility we must face up to: such understanding could ultimately be of help in order to achieve a safer ownership of our destinies, by individuating and reinforcing those cognitive firewalls that would prevent violence from always escalating and overflowing.

An account that analyzes the dynamic reasoning processes implicated in a fundamental problem of creativity in science: how does genuine novelty emerge from existing representations? How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural context of the problem; and dynamic processes of reasoning that extend ordinary cognition. Focusing on the third factor, Nersessian draws on cognitive science research and historical accounts of scientific practices to show how scientific and ordinary cognition lie on a continuum, and how problem-solving practices in one illuminate practices in the other. Her investigations of scientific practices show conceptual change as deriving from the use of analogies, imagistic representations, and thought experiments, integrated with experimental investigations and mathematical analyses. She presents a view of constructed models as hybrid objects, serving as intermediaries between targets and analogical sources in bootstrapping processes. Extending these results, she argues that these complex cognitive operations and structures are not mere aids to discovery, but that together they constitute a powerful form of reasoning—model-based reasoning—that generates novelty. This new approach to mental modeling and analogy, together with Nersessian's cognitive-historical approach, make Creating Scientific Concepts equally valuable to cognitive science and philosophy of science.