N.J. Nersessian – författare

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.

Einstein often expressed the sentiment that "the eternal mystery of the world is its comprehensibility," and that science is the means through which we comprehend it. However, nearly every­ one - including scientists - agrees that the concepts of modem physics are quite incomprehensible: They are both unintelligible to the educated lay-person and to the scientific community itself, where there is much dispute over the interpretation of even (and especially) the most basic concepts. There is, of course, almost universal agreement that modem science quite adequately accounts for and predicts events, i. e. , that its calculations work better than those of classical physics; yet the concepts of science are supposed to be descriptive of 'the world' as well - they should enable us to comprehend it. So, it is asked, and needs tobe"asked: Has modem physics failed in an important respect? It failed with me as a physics student. I came to physics, as with most naIve students, out of a desire to know what the world is really like; in particular, to understand Einstein's conception of it. I thought I had grasped the concepts in classical mechanics, but with electrodynamics confusion set in and only increased with relativity and quantum mechanics. At that point I began even to doubt whether I had really understood the basic concepts of classical mechanics.

The study of diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of traditional notions of reasoning such as classical logic. Understanding the contribution of modeling practices to discovery and conceptual change in science requires expanding 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 philosophy, 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. The term "model" comprises both internal and external representations. The models are intended as interpretations 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. Moreover, in the modeling process, various forms of abstraction are used.Evaluation and adaptation take place in light of structural, causal, and/or functional constraints. Model simulation can be used to produce new states and enable evaluation of behaviors and other factors. The various contributions of the book are written by interdisciplinary researchers who are active in the area of creative reasoning in science and technology, and are logically and computationally oriented: the most recent results and achievements about the topics above are illustrated in detail in this book.

Information technology has been, in recent years, under increasing commercial pressure to provide devices and systems which help/ replace the human in his daily activity. This pressure requires the use of logic as the underlying foundational workhorse of the area. New logics were developed as the need arose and new foci and balance has evolved within logic itself. One aspect of these new trends in logic is the rising impor­ tance of model based reasoning. Logics have become more and more tailored to applications and their reasoning has become more and more application dependent. In fact, some years ago, I myself coined the phrase "direct deductive reasoning in application areas", advocating the methodology of model-based reasoning in the strongest possible terms. Certainly my discipline of Labelled Deductive Systems allows to bring "pieces" of the application areas as "labels" into the logic. I therefore heartily welcome this important book to Volume 25 of the Applied Logic Series and see it as an important contribution in our overall coverage of applied logic.

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.

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.

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.

Einstein often expressed the sentiment that "the eternal mystery of the world is its comprehensibility," and that science is the means through which we comprehend it. However, nearly every­ one - including scientists - agrees that the concepts of modem physics are quite incomprehensible: They are both unintelligible to the educated lay-person and to the scientific community itself, where there is much dispute over the interpretation of even (and especially) the most basic concepts. There is, of course, almost universal agreement that modem science quite adequately accounts for and predicts events, i. e. , that its calculations work better than those of classical physics; yet the concepts of science are supposed to be descriptive of 'the world' as well - they should enable us to comprehend it. So, it is asked, and needs tobe"asked: Has modem physics failed in an important respect? It failed with me as a physics student. I came to physics, as with most naIve students, out of a desire to know what the world is really like; in particular, to understand Einstein's conception of it. I thought I had grasped the concepts in classical mechanics, but with electrodynamics confusion set in and only increased with relativity and quantum mechanics. At that point I began even to doubt whether I had really understood the basic concepts of classical mechanics.

For some time now the philosophy of science has been undergoing a major transfor­ mation. It began when the 'received view' of scientific knowledge -that developed by logical positivists and their intellectual descendants - was challenged as bearing little resemblance to and having little relevance for the understanding of real science. Subsequently, an overwhelming amount of criticism has been added. One would be hard-pressed to find anyone who would support the 'received view' today. Yet, in the search for a new analysis of scientific knowledge, this view continues to exert influence over the tenor of much of present-day philosophy of science; in particular, over its problems and its methods of analysis. There has, however, emerged an area within the discipline - called by some the 'new philosophy of science' - that has been engaged in transforming the problems and methods of philosophy of science. While there is far from a consensus of beliefs in this area, most of the following contentions would be affirmed by those working in it: - that science is an open-ended, on-going activity, whose character has changed significantly during its history - that science is not a monolithic enterprise - that good science can lead to false theories - that science has its roots in everyday circumstances, needs, methods, concepts, etc.

For some time now the philosophy of science has been undergoing a major transfor­ mation. It began when the ''received view'' of scientific knowledge -that developed by logical positivists and their intellectual descendants - was challenged as bearing little resemblance to and having little relevance for the understanding of real science. Subsequently, an overwhelming amount of criticism has been added. One would be hard-pressed to find anyone who would support the ''received view'' today. Yet, in the search for a new analysis of scientific knowledge, this view continues to exert influence over the tenor of much of present-day philosophy of science; in particular, over its problems and its methods of analysis. There has, however, emerged an area within the discipline - called by some the ''new philosophy of science'' - that has been engaged in transforming the problems and methods of philosophy of science. While there is far from a consensus of beliefs in this area, most of the following contentions would be affirmed by those working in it: - that science is an open-ended, on-going activity, whose character has changed significantly during its history - that science is not a monolithic enterprise - that good science can lead to false theories - that science has its roots in everyday circumstances, needs, methods, concepts, etc.

Einstein often expressed the sentiment that "the eternal mystery of the world is its comprehensibility," and that science is the means through which we comprehend it. However, nearly every­ one - including scientists - agrees that the concepts of modem physics are quite incomprehensible: They are both unintelligible to the educated lay-person and to the scientific community itself, where there is much dispute over the interpretation of even (and especially) the most basic concepts. There is, of course, almost universal agreement that modem science quite adequately accounts for and predicts events, i. e. , that its calculations work better than those of classical physics; yet the concepts of science are supposed to be descriptive of ''the world'' as well - they should enable us to comprehend it. So, it is asked, and needs tobe"asked: Has modem physics failed in an important respect? It failed with me as a physics student. I came to physics, as with most naIve students, out of a desire to know what the world is really like; in particular, to understand Einstein''s conception of it. I thought I had grasped the concepts in classical mechanics, but with electrodynamics confusion set in and only increased with relativity and quantum mechanics. At that point I began even to doubt whether I had really understood the basic concepts of classical mechanics.

Information technology has been, in recent years, under increasing commercial pressure to provide devices and systems which help/ replace the human in his daily activity. This pressure requires the use of logic as the underlying foundational workhorse of the area. New logics were developed as the need arose and new foci and balance has evolved within logic itself. One aspect of these new trends in logic is the rising impor­ tance of model based reasoning. Logics have become more and more tailored to applications and their reasoning has become more and more application dependent. In fact, some years ago, I myself coined the phrase "direct deductive reasoning in application areas", advocating the methodology of model-based reasoning in the strongest possible terms. Certainly my discipline of Labelled Deductive Systems allows to bring "pieces" of the application areas as "labels" into the logic. I therefore heartily welcome this important book to Volume 25 of the Applied Logic Series and see it as an important contribution in our overall coverage of applied logic.