Visual analogy is believed to be important in human problem solving. Yet, there are few computational models of visual analogy. In this paper, we present a preliminary computational model of visual analogy in problem solving. The model is instantiated in a computer program, called Galatea, which uses a language for representing and transferring visual information called Privlan. We describe how the computational model can account for a small slice of a cognitive-historical analysis of Maxwell’s reasoning about electromagnetism.

: This paper offers a preliminary analysis of conceptual change between event concepts. It begins with a brief review of the major findings of cognitive studies on event knowledge. The script model proposed by Schank and Abelson was the first attempt to represent event knowledge. Subsequent cognitive studies indicated that event knowledge is organized in the form of dimensional organizations in which temporally successive actions are related causally. This paper proposes a frame representation to capture and outline the internal structure (...) of event concepts, in particular, their causal connections. The frame representation offers an effective method to analyze the relations between event concepts, and to expose the unique cognitive mechanisms behind conceptual change involved event concepts. Finally this paper shows that the frame representation of event concepts is instrumental to understanding an important historical episode of conceptual change in the context of nineteenth-century optics. (shrink)

I propose a new perspective on the study of scientific revolutions. This is a transformation from an object-only perspective to an ontological perspective that properly treats objects and processes as distinct kinds. I begin my analysis by identifying an object bias in the study of scientific revolutions, where it takes the form of representing scientific revolutions as changes in classification of physical objects. I further explore the origins of this object bias. Findings from developmental psychology indicate that children cannot distinguish (...) processes from objects until the age of 7, but they have already developed a core system of object knowledge as early as 4 months of age. The persistence of this core system is responsible for the object bias among mature adults, i.e., the tendency to apply knowledge of physical objects to temporal processes. In light of the distinction between physical objects and temporal processes, I redraw the picture of the Copernican revolution. Rather than seeing it as a taxonomic shift from a geocentric to a heliocentric cosmology, we should understand it as a transformation from a conceptual system that was built around an object concept to one that was built around a process concept. (shrink)

In this paper we examine the pattern of conceptual change during scientific revolutions by using methods from cognitive psychology. We show that the changes characteristic of scientific revolutions, especially taxonomic changes, can occur in a continuous manner. Using the frame model of concept representation to capture structural relations within concepts and the direct links between concept and taxonomy, we develop an account of conceptual change in science that more adequately reflects the current understanding that episodes like the Copernican revolution are (...) not always abrupt. When concepts are represented by frames, the transformation from one taxonomy to another can be achieved in a piecemeal fashion not preconditioned by a crisis stage, and a new taxonomy can arise naturally out of the old frame instead of emerging separately from the existing conceptual system. This cognitive mechanism of continuous change demonstrates the constructive roles of anomaly and incommensurability in promoting the progress of science. (shrink)

Although “theory” has been the prevalent unit of analysis in the meta-study of science throughout most of the twentieth century, the concept remains elusive. I further explore the leitmotiv of several authors in this issue: that we should deal with theorizing (rather than theory) in biology as a cognitive activity that is to be investigated naturalistically. I first contrast how philosophers and biologists have tended to think about theory in the last century or so, and consider recent calls to upgrade (...) the role of theory in the life sciences against the background of the recent “data deluge” in molecular biology, systems biology, etc. I then review thinking about theory in biology in relation to physical theory as a positive or negative exemplar. I conclude by discussing various aspects of a positive program for “naturalizing theorizing.”. (shrink)

The discussion presents a framework of concepts that is intended to account for the rationality of semantic change and variation, suggesting that each scientific concept consists of three components of content: 1) reference, 2) inferential role, and 3) the epistemic goal pursued with the concept’s use. I argue that in the course of history a concept can change in any of these components, and that change in the concept’s inferential role and reference can be accounted for as being rational relative (...) to the third component, the concept’s epistemic goal. This framework is illustrated and defended by application to the history of the gene concept. It is explained how the molecular gene concept grew rationally out of the classical gene concept despite a change in reference, and why the use and reference of the contemporary molecular gene concept may legitimately vary from context to context. (shrink)

For historical epistemology to succeed, it must adopt a defensible set of categories to characterise scientific activity over time. In historically orientated philosophy of science during the twentieth century, the original categories of theory and observation were supplemented or replaced by categories like paradigm, research program and research tradition. Underlying all three proposals was talk about conceptual systems and conceptual structures, attributed to individual scientists or to research communities, however there has been little general agreement on the nature of these (...) structures. Recent experimental research in cognitive science has considerably refined the theory of concepts. Drawing upon the results of that research, philosophers can construct more concrete and empirically defensible representations of conceptual systems. I will suggest that this research supports a modest and useful sense of both normal and revolutionary science, not as epistemological continuities or discontinuities, but as particular patterns of conceptual change. (shrink)

The paper discusses three different ways of explaining the referential stability of concepts of physics. In order to be successful, an approach to referential stability has to provide resources to understand what constitutes the difference between the birth of a new concept with a history of its own, and an innovative step occurring within the lifetime of a persisting concept with stable reference. According to Theodore Arabatzis' 'biographical' approach (Representing Electrons 2006), the historical continuity of representations of the electron manifests (...) itself by the numerical stability of experimental parameters like the charge-to-mass ratio, and the continued acceptance of earlier experiments as manifestations of electron properties. I argue, against Arabatzis' approach, that the stability of experimental parameters justifies the assumption that there exists a chain of representations of a unique theoretical entity only if this stability occurs against the background of evidence for theoretical continuity. The Bain/Norton approach proposes to add exactly this element to the picture, but fails to reach its aim by focusing on formal similarities of Hamiltonians as an indicator of theoretical continuity. I shall argue that theoretical continuity has to be demonstrated rather on the level of particular solutions. This task is accomplished by the semantic embedding approach by means of defining a co-reference criterion for theoretical terms requiring the existence of semantic embedding relations between the terms that occur in particular solutions of different theories. (shrink)

The rationality of scientific concept formation in theory transitions, challenged by the thesis of semantic incommensurability, can be restored by theChains of Meaning approach to concept formation. According to this approach, concepts of different, succeeding theories may be identified with respect to referential meaning, in spite of grave diversity of the mathematical structures characterizing them in their respective theories. The criterion of referential identity for concepts is that they meet a relation ofsemantic embedding, i.e. that the embedding concept can be (...) substituted by the embedded one in classical limit situations. Three case studies from contemporary physics theories will be used to show that the Chains of Meaning approach not only yields meaning comparisons for already established concepts (as for Newtonian and Schwarzschild mass) but is also well suited to characterize actual scientific strategies of concept formation in yet open cases such as black hole entropy or relativistic thermodynamics. (shrink)

This article argues for a different outlook on the concept of extension, especially for the reference of general terms in scientific practice. Scientific realist interpretations of the two predominant theories of meaning, namely Descriptivism and Causal Theory, contend that a stable cluster of descriptions or an initial baptism fixes the extension of a general term such as a natural kind term. This view in which the meaning of general terms is presented as monosemantic and the referents as stable, homogeneous, and (...) unchangeable, however, does not reflect the various practices involved in the investigation of research materials and the related application of general terms in scientific practice. By drawing on the taxonomic diversity, particularly of structure-based classifications in chemical databases, this article illustrates the limited utility of such a concept of extension. Research materials often exhibit a plurality of material dimensions that, within different research contexts, allow for various and often equally significant taxonomic demarcations. In light of this, the extension of a general term cannot be uniquely determined by a supposedly independent nature of the referent but is relative to the model context under which the materials are investigated. This significance and plurality of the model context, I claim, needs to be mirrored in an account of meaning that is supposed to reflect scientific reality. On this account, the aim of this article is to present an alternative perspective on the concept of extension to accommodate the diverse material practices that determine the application of general terms in science. (shrink)

The main purpose of this dissertation is to examine critically and discuss the role of imagination in science and religion, with particular emphasis on its possible epistemic, creative, and meaning-making functions. In order to answer my research questions, I apply theories and concepts from contemporary philosophy of mind on scientific and religious practices. This framework allows me to explore the mental state of imagination, not as an isolated phenomenon but, rather, as one of many mental states that co-exist and interplay (...) in our cogntive architecture. Based on the philosophical discourse of philosophy of mind, four types of imagination are indentified and conceptualized: sensory, propositional, experiential, and creative imagination. These categories are then employed on five phenomena that can be found in scientific and religious environments: metaphors, models, thought experiments, aspect perception, and - in the religious case - rituals. In relation to the concept of religious "seeing" I consider how imaginings may influence visionary experiences and visualization, and compare these phenomena with cases of scientific visualization and eureka experiences. In regard to scientific and religious models, a distinction is made between, on the one hand, two notions of truth and, on the other hand, truth-independent meaning-making. In light of these categories, I differentiate between, and critically discuss, the use of imagination in doxastic, non-doxastic and fictionalist accounts. In light of this investigation, I formulate and defend the position of interactivism, which acknowledges a constant interplay between different attitudes and mental states. In my examination of rituals and scientific and religious thought experiments, special attention is given to the mental capacity to recreate the experiences that are entailed in an imagined scenario. At the end of the investigation, I consider the possible impact that my study might have on how we view science and religion as well as the dialogue bewteen these two fields. (shrink)

Central to Kuhn's notion of incommensurability are the ideas of meaning variance and lexicon, and the impossibility of translation of terms across different theories. Such a notion of incommensurability is based on a particular understanding of what a scientific language is. In this paper we first attempt to understand this notion of scientific language in the context of incommensurability. We consider the consequences of the essential multisemiotic character of scientific theories and show how this leads to even a single theory (...) being potentially 'internally incommensurable'. We then discuss Kuhn's lexicon-based approach to incommensurability and the problems associated with it. Finally we argue that this approach by Kuhn has interesting overlaps with the problem of meaning associated with multisemiosis, particularly the challenge of understanding the process of symbolization in scientific theories. (shrink)

A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...) scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination in problem-solving. (...) But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (shrink)

The important role of mathematical representations in scientific thinking has received little attention from cognitive scientists. This study argues that neglect of this issue is unwarranted, given existing cognitive theories and laws, together with promising results from the cognitive historical analysis of several important scientists. In particular, while the mathematical wizardry of James Clerk Maxwell differed dramatically from the experimental approaches favored by Michael Faraday, Maxwell himself recognized Faraday as “in reality a mathematician of a very high order,” and his (...) own work as in some respects a re‐representation of Faraday’s field theory in analytic terms. The implications of the similarities and differences between the two figures open new perspectives on the cognitive role of mathematics as a learned mode of representation in science. (shrink)

The history of the luminiferous ether is sketched with a view to ascertaining what factors may have kept this idea alive until 1905, when Einstein declared it superfluous.

This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)

We present an epistemological schema of natural sciences inspired by Peirce's pragmaticist view, stressing the role of the \emph{phenomenological map}, that connects reality and our ideas about it. The schema has a recognisable mathematical/logical structure which allows to explore some of its consequences. We show that seemingly independent principles as the requirement of reproducibility of experiments and the Principle of Sufficient Reason are both implied by the schema, as well as Popper's concept of falsifiability. We show that the schema has (...) some power in demarcating science by first comparing with an alternative schema advanced during the first part of the 20th century which has its roots in Hertz and has been developed by Einstein and Popper. Further, the identified differences allow us to focus in the construction of Special Relativity, showing that it uses an intuited concept of velocity that does not satisfy the requirements of reality in Peirce. While the main mathematical observation connected with this issue has been known for more than a century, it has not been investigated from an epistemological point of view. A probable reason could be that the socially dominating epistemology in physics does not encourage such line of work. We briefly discuss the relation of the abduction process presented in this work with discussions regarding ``abduction'' in the literature and its relation with ``analogy''. (shrink)

'Epistemological constructivism' holds that vision is mediated by background preconceptions and is theory-laden. Hence, two persons with differing theoretical commitments see the world differently and they could agree on what they see only if they both espoused the same conceptual framework. This, in its turn, undermines the possibility of theory testing and choice on a common theory-neutral empirical basis. In this paper, I claim that the cognitive sciences suggest that a part of vision may be only indirectly penetrated by cognition (...) in a way that does not threaten retrieval of information from a visual scene in a bottom-up way. That blocks the constructivist epistemological thesis. However, since spatial attention, which can be cognitively driven, seems to permeate all stages of visual processes, one is led to conclude that there is no part of vision immune to direct cognitive interference. Against this, I elaborate on the role of spatial attention and argue that it does influence vision in a top-down manner, but it does so only in an indirect way. I then argue that the existence of visual processes that are only indirectly penetrated by cognition undermines the epistemological conclusions of constructivism. (shrink)

This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These "model systems" are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive science that construes (...) cognition as occurring in a complex distributed system comprising people and artifacts, I argue that reasoning with model systems is a constraint satisfaction process involving co-construction, manipulation, and revision of mental and physical models. (shrink)

Cases where analogy has played a significant role in the formation of a new scientific concept are well-documented. Yet, how is it that genuinely new representations can be constructed from existing representations? It is argued that the process of ‘generic modeling’ enables abstraction of features common to both the domain of the source of the analogy and of the target phenomena. The analysis focuses on James Clerk Maxwell's construction of the electromagnetic field concept. The mathematical representation Maxwell constructed turned out (...) to be a system of abstract laws that when applied to electromagnetic systems yield laws of a dynamical system that will not map back onto the mechanicals domains used in their construction. (shrink)

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...) handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)