While collaboration has always played an important role in many cases of discovery and creation, recent developments such as the web facilitate and encourage collaboration at scales never seen before, even in areas such as mathematics, where contributions by single individuals have historically been the norm. This new scenario poses a challenge at the theoretical level, as it brings out the importance of various issues which, as of yet, have not been sufficiently central to the study of problem-solving, discovery, and (...) creativity. We analyze the case of collective and web-based proof events in mathematics, which share their temporal and social nature with every case of collective problem-solving. We propose that some ideas from cognitive architectures, in particular, the notion of codelet—understood as an agent engaged in one of a multitude of available tasks—can illuminate our understanding of collective problem-solving and act as a natural bridge from some of the theoretical aspects of collective, web-based discovery to the practical concern of designing cognitively inspired systems to support collective problem-solving. We use the Pythagorean Theorem and its many proofs as a case study to illustrate our approach. (shrink)

Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human (...) thought processes used to discover scientific laws. The programs - BACON, DALTON, GLAUBER, and STAHL - are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. "Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science. Pat Langley is an Associate Professor in the Department of Information and Computer Science at the University of California, Irvine.Herbert Simon is a Professor in the Departments of Psychology, Computer Science, and Philosophy at Carnegie-Mellon University. Gary L. Bradshaw is an Assistant Professor in the Department of Psychology and Institute of Cognitive Science at the University of Colorado, Boulder. Jan M. Zytkow is an Associate Professor in the Computer Science Department at Wichita State University. (shrink)

When two or more (groups of) researchers independently investigating the same domain arrive at the same result, a multiple discovery occurs. The pervasiveness of multiple discoveries in science suggests the intuition that they are in some sense inevitable—that one should view them as results that force themselves upon us, so to speak. We argue that, despite the intuitive force of such an “inevitabilist insight,” one should reject it. More specifically, we distinguish two facets of the insight and argue that: (...) (a) the profusion of multiple discoveries in scientific practice does not support the inevitabilist side of the inevitability/contingency of science controversy; and (b) the crucial role of background knowledge in scientific inquiry complicates the attempt to interpret the pervasiveness of multiple discoveries in realist terms. (shrink)

Kenneth F. Schaffner compares the practice of biological and medical research and shows how traditional topics in philosophy of science—such as the nature of theories and of explanation—can illuminate the life sciences. While Schaffner pays some attention to the conceptual questions of evolutionary biology, his chief focus is on the examples that immunology, human genetics, neuroscience, and internal medicine provide for examinations of the way scientists develop, examine, test, and apply theories. Although traditional philosophy of science has regarded scientific discovery—the (...) questions of creativity in science—as a subject for psychological rather than philosophical study, Schaffner argues that recent work in cognitive science and artificial intelligence enables researchers to rationally analyze the nature of discovery. As a philosopher of science who holds an M.D., he has examined biomedical work from the inside and uses detailed examples from the entire range of the life sciences to support the semantic approach to scientific theories, addressing whether there are "laws" in the life sciences as there are in the physical sciences. Schaffner's novel use of philosophical tools to deal with scientific research in all of its complexity provides a distinctive angle on basic questions of scientific evaluation and explanation. (shrink)

Finding causes is a central goal in psychological research. In this paper, I argue based on the interventionist approach to causal discovery that the search for psychological causes faces great obstacles. Psychological interventions are likely to be fat-handed: they change several variables simultaneously, and it is not known to what extent such interventions give leverage for causal inference. Moreover, due to problems of measurement, the degree to which an intervention was fat-handed, or more generally, what the intervention in fact did, (...) is difficult to reliably estimate. A further complication is that the causal findings in psychology are typically made at the population level, and such findings do not allow inferences to individual-level causal relationships. I also discuss the implications of these problems for research, as well as various ways of addressing them, such as focusing more on the discovery of robust but non-causal patterns. (shrink)

Ever since Newton created dynamics, there has been controversy about its foundations. Are space and time absolute? Do they form a rigid but invisible framework and container of the universe? Or are space, time, and motion relative? If so, does Newton's 'framework' arise through the influence of the universe at large, as Ernst Mach suggested? Einstein's aim when creating his general theory of relativity was to demonstrate this and thereby implement 'Mach's Principle'. However, it is widely believed that he achieved (...) only partial success. This question of whether motion is absolute or relative has been a central issues in philosophy; the nature of time has perennial interest. Current attempts to create a quantum description of the whole universe keep these issues at the cutting edge of modern research. Written by the world's leading expert on Mach's Principle, The Discovery of Dynamics is a highly original account of the development of notions about space, time, and motion. Widely praised in its hardback version, it is one of the fullest and most readable accounts of the astronomical studies that culminated in Kepler's laws of planetary motion and of the creation of dynamics by Galileo, Descartes, Huygens, and Newton. Originally published as Absolute or Relative Motion?, Vol. 1: The Discovery of Dynamics, The Discovery of Dynamics provides the technical background to Barbour's recently published The End of Time, in which he argues that time disappears from the description of the quantum universe. (shrink)

On Discovery became a key reference for anyone who wanted to know about "firsts" in theology, philosophy, science, technology, literature, language, law, material culture, and other fields. Polydore took his information from dozens of Greek, Roman, biblical, and Patristic authorities. His main point was to show that many Greek and Roman claims for discovery were false and that ancient Jews or other Asian peoples had priority.

The distinction between discovery and justification is ambiguous. This obscures the debate over a logic of discovery. For the debate presupposes the distinction. Real discoveries are well established. What is well established is justified. The proper distinctions are three: initial thinking, plausibility, and acceptability. Logic is not essential to initial thinking. We do not need good supporting reasons to initially think of an hypothesis. Initial thoughts need be neither plausible nor acceptable. Logic is essential, as Hanson noted, to both (...) plausibility and acceptability. An hypothesis needs good supporting reasons to be either plausible or acceptable. Such reasons need not be relative to the particular scientific theory undergoing test at the time. There is no fundamental difference between reasons relevant to plausibility and acceptability. The difference is one of degree. Acceptability requires more than plausibility. (shrink)

Scientists routinely solve the problem of supplementing one’s store of variables with new theoretical posits that can explain the previously inexplicable. The banality of success at this task obscures a remarkable fact. Generating hypotheses that contain novel variables and accurately project over a limited amount of additional data is so difficult—the space of possibilities so vast—that succeeding through guesswork is overwhelmingly unlikely despite a very large number of attempts. And yet scientists do generate hypotheses of this sort in very few (...) tries. I argue that this poses a dilemma: either the long history of scientific success is a miracle, or there exists at least one method or algorithm for generating novel hypotheses with at least limited projectibility on the basis of what’s available to the scientist at a time, namely a set of observations, the history of past conjectures, and some prior theoretical commitments. In other words, either ordinary scientific success is miraculous or there exists a logic of discovery at the heart of actual scientific method. (shrink)

In distinguishing justification from discovery, the logical empiricists hoped to avoid confusing causal matters with normative ones. Exaggerating the virtue of this distinction, however, has disguised from us important features of the concept of a reason as it functions in human practice. Surfacing those features gives some insight into reasoning and argument.

In the paper I explore the relations between a relatively new and quickly expanding branch of artificial intelligence –- the automated discovery systems –- and some new views advanced in the old debate over scientific realism. I focus my attention on one such system, GELL-MANN, designed in 1990 at Wichita State University. The program's task was to analyze elementary particle data available in 1964 and formulate an hypothesis (or hypotheses) about a `hidden', more simple structure of matter, or to put (...) it in contemporary terms –- the discovery of quarks. The central thesis of my paper is that systems like GELL-MANN not only discover (or rediscover) the hidden structure of matter, but also provide independent strong evidence in favor of scientific realism about entities involved in that structure. I make an attempt to show how an argument for scientific realism about sub-microscopic entities can be constructed that would parallel Ian Hacking's `argument from coincidence' presented with respect to microscopic objects in his famous book Representing and Intervening. (shrink)

The LNAI series reports state-of-the-art results in artificial intelligence research, development, and education, at a high level and in both printed and electronic form.

In this paper I consider two accounts of scientific discovery, Robert Hudson's and Peter Achinstein's. I assess their relative success and I show that while both approaches are similar in promising ways, and address experimental discoveries well, they could address the concerns of the discovery sceptic more explicitly than they do. I also explore the implications of their inability to address purely theoretical discoveries, such as those often made in mathematical physics. I do so by showing that extending (...) Hudson's or Achinstein's account to such cases can sometimes provide a misleading analysis about who ought to be credited as a discoverer. In the final sections of the paper I work out some revisions to the Hudson/Achinstein account by drawing from a so-called structural realist view of theory change. Finally, I show how such a modified account of discovery can answer sceptical critics such as Musgrave or Woolgar without producing misleading analyses about who ought to receive credit as a discoverer in cases from the mathematical sciences. I illustrate the usefulness of this approach by providing an analysis of the case of the discovery of the Casimir effect. (shrink)

This research deals with a very important topic, which is modern discoveries and their impact on jurists. I have dealt with the concept of modern discoveries and their impact on the science of objectives, and the relationship of modern discoveries to the science of objectives. I have dealt with applications of the impact of modern discoveries on jurists, namely the ruling on artificial insemination, egg transfer, embryo freezing, and the adoption of astronomical calculations in determining the (...) times and beginning of lunar months. These applications are a serious study of the questioning about these issues in our present time. (shrink)

Given a set of objects characterized by a number of attributes, hidden patterns can be discovered in them for the grouping of similar objects into clusters. If each of these clusters can be considered as exemplifying a certain concept, then the problem concerned can be referred to as a concept discovery problem. This concept discovery problem can be solved to some extent by existing data clustering techniques. However, they may not be applicable when the concept involved is vague in nature (...) or when the attributes characterizing the objects can be qualitative, quantitative, and fuzzy at the same time. To discover such concepts from objects with such characteristics, we propose a Genetic-Algorithm-based technique. By encoding a specific object grouping in a chromosome and a fitness measure to evaluate the cluster quality, the proposed technique is able to discover meaningful fuzzy clusters and assign membership degrees to objects that do not fully exemplify a certain concept. For evaluation, we tested the proposed technique with simulated and real data and the results are found to be very promising. (shrink)

The main message of this volume is that the creative process of discovery is not a purely rational enterprise in the traditional sense which equates rationality with logical reasoning, yet it is a manifestation of a universal phenomenon ...

The discovery of the Higgs particle required a signal of 5σ significance. The rigid application of that condition is a convention that disregards more specific aspects of the given experiment. In particular, it does not account for the characteristics of the look elsewhere effect in the individual experimental context. The paper relates this aspect of data analysis to the question as to what extent theoretical reasoning should be admitted to play a role in the assessment of the significance of empirical (...) data. (shrink)

Reichenbach's well-known distinction between the context of discovery and the context of justification has recently come under attack from several quarters. In this paper I attempt to reconsider the distinction and evaluate various recent criticisms of it. These criticisms fall into two main groups: those which directly challenge Reichenbach's distinction; and those which (I argue) indirectly but no less seriously challenge that distinction by rejecting the related distinction between psychology and epistemology, and defending the "naturalizing" of epistemology. I argue that (...) these recent criticisms fail, and that the distinction remains an important conceptual tool necessary for an adequate understanding of the way in which scientific claims purport to appropriately portray our natural environment. (shrink)

Human and machine discovery are gradual problem-solving processes of searching large problem spaces for incompletely defined goal objects. Research on problem solving has usually focused on search of an instance space (empirical exploration) and a hypothesis space (generation of theories). In scientific discovery, search must often extend to other spaces as well: spaces of possible problems, of new or improved scientific instruments, of new problem representations, of new concepts, and others. This paper focuses especially on the processes for finding new (...) problem representations and new concepts, which are relatively new domains for research on discovery.Scientific discovery has usually been studied as an activity of individual investigators, but these individuals are positioned in a larger social structure of science, being linked by the blackboard of open publication (as well as by direct collaboration). Even while an investigator is working alone, the process is strongly influenced by knowledge and skills stored in memory as a result of previous social interaction. In this sense, all research on discovery, including the investigations on individual processes discussed in this paper, is social psychology, or even sociology. (shrink)

This habilitation thesis explores the foundations of scientific discovery by examining the roles of language, conceptual structures, and artificial intelligence in knowledge production. It contributes to the emerging field of the philosophy of scientific discovery by addressing fundamental questions: What constitutes a scientific discovery? What structural features characterize discovery processes? How do language and naming practices shape scientific progress? And to what extent can machines participate in or even independently generate discoveries? Drawing from case studies in biology, epistemology, and (...) AI research, this work argues that scientific discovery is a structured process encompassing three core elements: finding, acceptance, and knowledge. Special attention is given to declarative speech acts in the validation of discoveries, the role of ambiguity and naming in the evolution of scientific terminology, and the potential for artificial agents to engage in meaning-making and scientific inference. By integrating perspectives from the philosophy of science, language, and mind, this work lays the groundwork for a systematic and interdisciplinary approach to understanding scientific discovery. (shrink)

This habilitation thesis explores the foundations of scientific discovery by examining the roles of language, conceptual structures, and artificial intelligence in knowledge production. It contributes to the emerging field of the philosophy of scientific discovery by addressing fundamental questions: What constitutes a scientific discovery? What structural features characterize discovery processes? How do language and naming practices shape scientific progress? And to what extent can machines participate in or even independently generate discoveries? Drawing from case studies in biology, epistemology, and (...) AI research, this work argues that scientific discovery is a structured process encompassing three core elements: finding, acceptance, and knowledge. Special attention is given to declarative speech acts in the validation of discoveries, the role of ambiguity and naming in the evolution of scientific terminology, and the potential for artificial agents to engage in meaning-making and scientific inference. By integrating perspectives from the philosophy of science, language, and mind, this work lays the groundwork for a systematic and interdisciplinary approach to understanding scientific discovery. (shrink)

European thought begins with the Greeks. Scientific and philosophic thinking--the pursuit of truth and the grasping of unchanging principles of life--is a historical development, an achievement; and, as Bruno Snell writes in The Discovery of the Mind, nothing less than a revolution. The Greeks did not take mental resources already at their disposal and merely map out new subjects for discussion and investigation. In poetry, drama, and philosophy they in fact discovered the human mind. The stages in man's gradual understanding (...) of himself are revealed in the course of ancient literature from Homer to Virgil. A rational view of the nature of man slowly established itself in the creations of epic and lyric poetry, tragedy and literary criticism, pre-Socratic thought, and early Greek ethics all the way to the discovery of humanitas and the spiritual landscape of Virgil's Arcadia. The Discovery of the Mind is a landmark work in tracing this evolution of consciousness--one of the distinguishing characteristics of the history of man. (shrink)

What constitutes a scientific discovery? What role do discoveries play in science, its dynamics and social practices? Must every discovery be attributed to an individual discoverer (or a small number of discoverers)? The paper explores these questions by first critically examining extant philosophical explications of scientific discovery—the models of scientific discovery, propounded by Kuhn, McArthur, Hudson, and Schindler. As a simple, natural and powerful alternative, we proffer the “change-driver model”: in a nutshell, it takes discoveries to be cognitive (...) scientific results that have epistemically advanced science. The model overcomes the shortcomings of its precursors, whilst preserving their insights. We demonstrate its intensional and extensional superiority, especially with respect to the link between scientific discoveries and the dynamics of science, as well as the award system of science. Both as an illustration, and as an application to a recent scientific and political controversy, we apply the considered models of discovery to one of the most momentous discoveries of science: the expansion of the universe. We oppose the 2018 proposal of the International Astronomers’ Union as too simplistic vis-`a-vis the historical complexity of the episode. The change- driver model yields a more nuanced and circumspect verdict: (i) The redshift-distance relation shouldn’t be named the “Hubble-Lemaître Law”, but “Slipher-Lundmark-Hubble-Humason Law”; (ii) Its interpretation in terms of an expanding universe, however, Lemaître ought to be given credit for; but (iii) The establishment of the expansion of the universe, as an evidentially sufficiently warranted result, is a communal achievement, emerging in the 1950s or 1960s. (shrink)

The history of science is articulated by moments of discovery. Yet, these 'moments' are not simple or isolated events in science. Just as a scientific discovery illuminates our understanding of nature or of society, and reveals new connections among phenomena, so too does the history of scientific activity and the analysis of scientific reasoning illuminate the processes which give rise to moments of discovery and the complex network of consequences which follow upon such moments. Understanding discovery has not been, until (...) recently, a major concern of modem philosophy of science. Whether the act of discoyery was regarded as mysterious and inexplicable, or obvious and in no need of explanation, modem philosophy of science in effect bracketed the question. It concentrated instead on the logic of scientific explanation or on the issues of validation or justification of scientific theories or laws. The recent revival of interest in the context of discovery, indeed in the acts of discovery, on the part of philosophers and historians of science, represents no one particular method'ological or philosophical orientation. It proceeds as much from an empiricist and analytical approach as from a sociological or historical one; from considerations of the logic of science as much as from the alogical or extralogical contexts of scientific tho'¢tt and practice. But, in general, this new interest focuses sharply on the actual historical and contem porary cases of scientific discovery, and on an examination of the act or moment of discovery in situ. (shrink)

Observational and experimental discoveries of new factual entities such as objects, systems, or processes, are major contributors to some advances in the life sciences. Yet, whereas discovery of theories was extensively deliberated by philosophers of science, very little philosophical attention was paid to the discovery of factual entities. This paper examines historical and philosophical aspects of the experimental discovery by Carl Woese of archaea, prokaryotes that comprise one of the three principal domains of the phylogenetic tree. Borrowing Kuhn’s terminology, (...) this discovery of a major biological entity was made during a ‘normal science’ project of building molecular taxonomy for prokaryotes. Unexpectedly, however, an observed anomaly instigated the discovery of archaea. Substantiation of the existence of the new archaeal entity and consequent reconstruction of the phylogenetic tree prompted replacement of a long-held model of a prokarya and eukarya bipartite tree of life by a new model of a tripartite tree comprising of bacteria, archaea, and eukarya. This paper explores the history and philosophical implications of the progression of Woese’s project from normal science to anomaly-instigated model-changing discovery. It is also shown that the consequential discoveries of RNA splicing and of ribozymes were similarly prompted by unexpected irregularities during normal science activities. It is thus submitted that some discoveries of factual biological entities are triggered by unforeseen observational or experimental anomalies. (shrink)

Citation data have become an increasingly significant source of information for historians, sociologists, and other researchers studying the evolution of science. In the past few decades elaborate methodologies have been developed for the use of citation data in the study of the modern history of science. This article focuses on how citation indexes make it possible to trace the background and development of discoveries as well as to assess the credit that publishing scientists assign to particular discoverers. Kuhn's notion (...) of discovery is discussed. The priority dispute over the discovery of the AIDS virus is used as an example. (shrink)

Aristotle's Categories can easily seem to be a statement of a naïve, pre-philosophical ontology, centered around ordinary items. Wolfgang-Rainer Mann argues that the treatise, in fact, presents a revolutionary metaphysical picture, one Aristotle arrives at by (implicitly) criticizing Plato and Plato's strange counterparts, the "Late-Learners" of the Sophist. As Mann shows, the Categories reflects Aristotle's discovery that ordinary items are things (objects with properties). Put most starkly, Mann contends that there were no things before Aristotle. The author's argument consists of (...) two main elements. First, a careful investigation of Plato which aims to make sense of the odd-sounding suggestion that things do not show up as things in his ontology. Secondly, an exposition of the theoretical apparatus Aristotle introduces in the Categories--an exposition which shows how Plato's and the Late-Learners' metaphysical pictures cannot help but seem inadequate in light of that apparatus. In doing so, Mann reveals that Aristotle's conception of things--now so engrained in Western thought as to seem a natural expression of common sense--was really a hard-won philosophical achievement. Clear, subtle, and rigorously argued, The Discovery of Things will reshape our understanding of some of Aristotle's--and Plato's--most basic ideas. (shrink)

"A discussion of the historical development of our ideas of time as they relate to nature, human nature and society. . . . The excellence of The Discovery of Time is unquestionable."--Martin Lebowitz, The Kenyon Review.

The way scientific discovery has been conceptualized has changed drastically in the last few decades: its relation to logic, inference, methods, and evolution has been deeply reloaded. The ‘philosophical matrix’ moulded by logical empiricism and analytical tradition has been challenged by the ‘friends of discovery’, who opened up the way to a rational investigation of discovery. This has produced not only new theories of discovery, but also new ways of practicing it in a rational and more systematic way. Ampliative rules, (...) methods, heuristic procedures and even a logic of discovery have been investigated, extracted, reconstructed and refined. The outcome is a ‘scientific discovery revolution’: not only a new way of looking at discovery, but also a construction of tools that can guide us to discover something new. This is a very important contribution of philosophy of science to science, as it puts the former in a position not only to interpret what scientists do, but also to provide and improve tools that they can employ in their activity. (shrink)

In this paper, I want to substantiate three related claims regarding causal discovery from non-experimental data. Firstly, in scientific practice, the problem of ignorance is ubiquitous, persistent, and far-reaching. Intuitively, the problem of ignorance bears upon the following situation. A set of random variables V is studied but only partly tested for (conditional) independencies; i.e. for some variables A and B it is not known whether they are (conditionally) independent. Secondly, Judea Pearl’s most meritorious and influential algorithm for causal discovery (...) (the IC algorithm) cannot be applied in cases of ignorance. It presupposes that a full list of (conditional) independence relations is on hand and it would lead to unsatisfactory results when applied to partial lists. Finally, the problem of ignorance is successfully treated by means of ALIC, the adaptive logic for causal discovery presented in this paper. (shrink)

Building on William G. Lycan’s insight that proper names are paronymous, I pursue two goals in this paper: I argue that Lycan’s insight is not restricted to proper names, but can be extended to include certain general terms, and I aim to demonstrate how this contributes to a better understanding of sentences in the context of scientific discovery. To this end, I first address the question of how to best grasp the largely unknown concept of paronymy by tracing it back (...) to Aristotle, and by exploring recent developments in the philosophy of language and in linguistics. I then focus in greater detail on Lycan’s argument that proper names are paronymous and extend this reasoning to general terms, using analogous examples to show that general terms, like proper names, exhibit paronymy. Shifting the focus to scientific discovery, I show how recognizing the paronymy of general terms enhances our understanding of how scientific terms evolve over time and relate to other terms. My analysis also reveals that the “is” in scientific sentences does not necessarily function as the “is” of identity but can, among others, also be interpreted as the “is” of explication. This allows not only for the resolution of various puzzles, but also for different readings of sentences to coexist peacefully. (shrink)

The relationship between Peircean abduction and the modern notion of Inference to the Best Explanation is a matter of dispute. Some philosophers, such as Harman :88–95, 1965) and Lipton, claim that abduction and IBE are virtually the same. Others, however, hold that they are quite different :503, 1998; Minnameier in Erkenntnis 60:75–105, 2004) and there is no link between them :419–442, 2009). In this paper, I argue that neither of these views is correct. I show that abduction and IBE have (...) important similarities as well as differences. Moreover, by bringing a historical perspective to the study of the relationship between abduction and IBE—a perspective that is lacking in the literature—I show that their differences can be well understood in terms of two historic developments in the history of philosophy of science: first, Reichenbach’s distinction between the context of discovery and the context of justification—and the consequent jettisoning of the context of discovery from philosophy of science—and second, underdetermination of theory by data. (shrink)

‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in (...) science as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

How do scientific models represent in a way that enables us to discover new truths about reality and draw inferences about it? Contemporary accounts of scientific discovery answer this question by focusing on the cognitive mechanisms involved in the generation of new ideas and concepts in terms of a special sort of reasoning—or model-based reasoning—involving imagery. Alternatively, I argue that answering this question requires that we recognise the crucial role of the propositional imagination in the construction and development of models (...) for the purpose of generating hypotheses that are plausible candidates for truth. I propose simple fictionalism as a new account of models as Waltonian games of make-believe and suggest that models can lead to genuine scientific discovery when they are used as representations that denote real world phenomena and generate two main kinds of theoretical hypotheses, model-world comparisons and direct attributions. (shrink)

The defining insight of evolutionary psychology consists of bringing considerations drawn from evolutionary biology to bear on the study of human psychology. So characterized, evolutionary psychology encompasses a large range of views about the nature and evolution of human psychology as well as diverging opinions about the proper method for studying them.¹ In this article, I propose to clarify and evaluate various aspects of evolutionary psychologists’ methodology, with a special focus on their heuristics of discovery—i.e., their methods for developing plausible (...) hypotheses—and their strategies of confirmation—i.e., their methods for providing empirical support for these hypotheses.² I will also evaluate several well-known objections raised against evolutionary psychology. Note that because views about psychology and evolution differ among evolutionary psychologists, I do not pretend to cover every method used in evolutionary psychology.³. (shrink)

This thesis presents an alternative method for the detection of MIMIC models. Previous methods (such as factor analysis) suffer from a number of significant aws and limitations, which the new method (a causal search algorithm) doesn't suffer. A new algorithm is introduced, followed by a worked-through example of its application. Discussion focuses on some of the limiting assumptions the algorithm currently requires. Finally, recommendations for future work address improvements of the algorithm, as well as its applicability.

This study compares Pairs of subjects with Single subjects in a task of discovering scientific laws with the aid of experiments. Subjects solved a molecular genetics task in a computer micro‐world (Dunbar, 1993). Pairs were more successful in discovery than Singles and participated more actively in explanatory activities (i.e., entertaining hypotheses and considering alternative ideas and justifications). Explanatory activities were effective for discovery only when the subjects also conducted crucial experiments. Explanatory activities were facilitated when paired subjects made requests of (...) each other for explanation and focused on them. The study extends from individual to collaborative discovery activities the importance to the discovery process of setting goals to find hypotheses and evidence (Dunbar, 1993) and to construct explanations of phenomena and processes encountered in examples (Chi, Bassok, Lewis, & Glaser, 1989). (shrink)

The discovery of the signal peptides that direct proteins to localize at the nucleolus is described here. The nucleolar targeting signal termed the NOS consists of clustered basic amino acids organized such that a portion also functions as the nuclear transporting signal. Although a NOS has been identified within the regulatory genes of human retroviruses, HTLV‐I and HIV‐I, signals of similar function in cellular proteins – such as heat shock proteins – may be induced through the configurational change of protein (...) structure by heat or stress. (shrink)

Molecular chaperones assist de novo protein folding and facilitate the refolding of stress‐denatured proteins. The molecular chaperone concept was coined nearly 35 years ago, and since then, tremendous strides have been made in understanding how these factors support protein folding. Here, we focus on how various chaperone proteins were first identified to play roles in protein folding. Examples are used to illustrate traditional routes of chaperone discovery and point out their advantages and limitations. Recent advances, including the development of folding (...) biosensors and promising methods for the stabilization of proteins in vivo, provide new routes for chaperone discovery. (shrink)

I will examine the first of Thomas Kuhn’s Thalheimer Lectures delivered in 1984, with the purpose of establishing a connection between Kuhn’s historiographical thought and his criticism of the traditional distinction between the context of discovery and the context of justification, or, as I call it, the DJ distinction. In order to do this, I will start by exploring the Kuhnian view of the so-called static approach in philosophy of science, taking as my main reference the work of Bacon, Descartes, (...) and foundationalist epistemology. I will continue by examining the relationship between Kuhnian historiography and the DJ distinction, comparing the first Thalheimer Lecture with other texts published by Kuhn. Finally, I will assert that Kuhn’s rejection of the DJ distinction is the result of adopting a historiographical matrix whose philosophical consequences are irreconcilable with the static approach in history and philosophy of science, for which the DJ distinction is essential. (shrink)