This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

In the past few years, social epistemologists have developed several formal models of the social organisation of science. While their robustness and representational adequacy has been analysed at length, the function of these models has begun to be discussed in more general terms only recently. In this article, I will interpret many of the current formal models of the scientific community as representing the latest development of what I will call the ‘Kuhnian project’. These models share with (...) Kuhn a number of questions about the relation between individuals and communities. At the same time, they also inherit some of Kuhn’s problematic characterisations of the scientific community. In particular, current models of the social organisation of science represent the scientific community as essentially value-free. This may put into question both their representational adequacy and their normative ambitions. In the end, it will be shown that the discussion on the formal models of the scientific community may contribute in fruitful ways to the ongoing debates on value judgements in science. (shrink)

Formal models of scientific inquiry, aimed at capturing socio-epistemic aspects underlying the process of scientific research, have become an important method in formal social epistemology and philosophy of science. In this introduction to the special issue we provide a historical overview of the development of formal models of this kind and analyze their methodological contributions to discussions in philosophy of science. In particular, we show that their significance consists in different forms of ‘methodological iteration’ whereby (...) the models initiate new lines of inquiry, isolate and clarify problems with existing knowledge claims, and stimulate further research. (shrink)

Having a satisfactory definition of behavioural deception is important for understanding several types of evolutionary questions. No definition offered in the literature so far is adequate on all fronts. After identifying characteristics that are important for a definition, a new definition of behavioural deception is offered. The new definition, like some other proposed attempts, relies on formal game-theoretic models of signalling. Unlike others, it incorporates explicit consideration of the population in which the potentially deceptive interactions occur. The general structure (...) of the definition satisfies many of the characteristics that were problematic for other definitions, and others are satisfied by explicitly incorporating information about the population in which interactions occur. Examples are given for chick begging in the Sir Philip Sidney game and other situations. 1 Introduction2 Deception in Formal Models2.1 Formal models of signalling2.2 Deception as dishonesty2.3 Deception as negative value of information2.4 Deception as misinformation with payoff conditions3 A Revised Definition3.1 Technical definitions3.2 Begging behaviour and the Sir Philip Sidney game3.3 ‘Universal’ deception and a possible objection3.4 One-on-one interactions3.5 Lucky errors4 Discussion and Conclusions. (shrink)

The opportunity cost model (OCM) aims to explain various phenomena, among which the finding that performance degrades if executive functions are used repeatedly (). We argue that an OCM account of resource depletion requires two unlikely assumptions, and we discuss an alternative that does not require these assumptions. This alternative model describes the interplay between executive function and motivation.

This paper's purpose is to set forth the conditions of explanation in the domain of formal modelling of social action. Explanation is defined as an adequate account of the underlying factors bringing about a phenomenon. The modelling of a social phenomenon can claim explanatory value in this sense if the following two conditions are fulfilled. (1) The generative mechanisms involved translate the effects of real factors abstracted from their phenomenal context, not those of purely ideal ones. (2) (...) The explanatory hypotheses, which account for the effects of explanatory factors, and the purely descriptive hypotheses, which introduce conceptual simplifications and summarise complex secondary mechanisms, are relatively independent from each other with regard to the phenomenon represented. This condition subjects the model to testing by alternatives through the development of purely descriptive hypotheses in the sense of explanatory or analytical realism. (shrink)

Awareness is a concept that has been frequently studied in the context of Computer Supported Cooperative Work. However, other fields of computer science can benefit from this concept. Recent research in the multi-agent systems field has highlighted the relevance of complex interaction models such as multi-party communication and context awareness for simulation and adaptive systems. In this article, we present a generic interaction model that enables to use these different models in a standardized way. Emerging as a first-order abstraction, (...) the environment, in the sense of a common medium for the agents, is a suitable paradigm to support the agents’ awareness. We present an operational model, called Environment as Active Support of Interaction, to take into account all the agents that can be interested in a communication. This model is then extended for the regulation of multiagent systems interactions. Priority policies are given to manage the rules governing the context (un-)awareness of the agents. We also present a new AUML connector to create protocols that take into account the agent awareness to implement proactive behaviour, and several communication scenarios are proposed to show practical applications of this model. (shrink)

One way of dealing with the proliferation of conjectures that accompany the diverse study of the evolution of language is to develop precise and testable models which reveal otherwise latent implications. We suggest how verbal theories of the role of individual development in language evolution can benefit from formal modeling, and vice versa.

I. The function of models in the empirical sciencesII. Structure and purpose: conditions of a structural nature which models should satisfy in order to accomplish their function.III. Generalisation and specialisation of the classical definition of model, in view of the above requirements:the algebraic model conceptthe semantic model conceptthe syntactical model conceptIV. Attempt towards reunification: the concept of model on a pragmatic basis.

What is the relation or connection between formalizations of induction and the actual inductive inferences of scientists? Building from recent works in the philosophy of logic, this paper argues that these formalizations of induction are best viewed as models and not literal descriptions of inductive inferences in science. Three arguments are put forward to support this claim. First, I argue that inductive support is the kind of phenomenon that can be justifiably modeled. Second, I argue that these formalizations have (...) the features that define models—that they have representors, artefacts, and idealizations. Third, I argue that these formalizations being models explains their plurality and revisability. (shrink)

This unique book presents a comprehensive and rigorous treatment of the theory of computability which is introductory yet self-contained. It takes a novel approach by looking at the subject using computation models rather than a limitation orientation, and is the first book of its kind to include software. Accompanying software simulations of almost all computational models are available for use in conjunction with the text, and numerous examples are provided on disk in a user-friendly format. Its applications to computer (...) class='Hi'>science itself include interesting links to programming language theory, compiler design theory, and algorithm design. The software, numerous examples, and solutions make this book ideal for self-study by computer scientists and mathematicians alike. (shrink)

Thagard presented a framework for conceptual change in science based on conceptual systems. Thagard challenged belief revision theorists, claiming that traditional belief-revision systems are able to model only the two most conservative types of changes in his framework, but not the more radical ones. The main aim of this work is to take up Thagard’s challenge, presenting a belief-revision-like system able to mirror radical types of conceptual change. We will do that with a conceptual revision system, i.e. a belief-revision-like (...) system that takes conceptual structures as units of revisions. We will show how our conceptual revision and contraction operations satisfy analogous of the AGM postulates at the conceptual level and are able to mimic Thagard’s radical types of conceptual change. (shrink)

The grammatical paradigm used to be a model for entire areas of cognitive science. Its primary tenet was that theories are axiomatic-like systems. A secondary tenet was that their predictions should be tested quickly and in great detail with introspective judgments. While the grammatical paradigm now often seems passé, we argue that in fact it continues to be as efficient as ever. Formal models are essential because they are explicit, highly predictive, and typically modular. They make numerous critical (...) predictions, which must be tested efficiently; introspective judgments do just this. We further argue that the grammatical paradigm continues to be fruitful. Within linguistics, implicature theory is a recent example, with a combination of formal explicitness, modularity, and interaction with experimental work. Beyond traditional linguistics, the grammatical paradigm has proven fruitful in the study of gestures and emojis; literature (“Free Indirect Discourse”); picture semantics and comics; music and dance cognition; and even reasoning and concepts. We argue, however, that the grammatical paradigm must be adapted to contemporary cognitive science. Computational methods are essential to derive quantitative predictions from formal models (Bayesian pragmatics is an example). And data collection techniques offer an ever richer continuum of options, from introspective judgments to large-scale experiments, which makes it possible to optimize the cost/benefit ratio of the empirical methods that are chosen to test theories. (shrink)

David Hull’s book (1988) provides an evolutionary account of the development of science which pays attention to both the social and conceptual aspects of that process. Unlike most philosophers who only invoke Darwinian metaphors in a casual way, Hull takes the analogy between the biological evolution of species and the growth of scientific knowledge quite seriously and by providing abstract definitions of terms such as replicator, interactor and lineage, he makes it possible for us to see clearly the structural (...) similarities between the two historical processes.Other symposiasts will comment on how tight that analogy really is. I must remark in passing that I have never understood the intense interest which evolutionary epistemologists take in this comparison. Surely our major job is to understand how science works, perhaps by using evolutionary theory as a fallible heuristic, but nothing seems to hinge on the extent of the formal analogy. (shrink)

To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane :951–961, 1987) and introduce some dynamic properties of the respiratory system. The passive elements are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles force is applied to both compartments. Parameters of the model are identified in using experimental data of airflow signal measured by pneumotachography (...) and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R2 ≥ 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing. (shrink)

I am arguing that it is only by concentrating on the role of models in theory construction, interpretation and change, that one can study the progress of science sensibly. I define the level at which these models operate as a level above the purely empirical (consisting of various systems in reality) but also indeed below that of the fundamental formal theories (expressed linguistically). The essentially multi-interpretability of the theory at the general, abstract linguistic level, implies that it can (...) potentially make claims about systems in reality, other than the particular one which originally induced it. Any so-called correspondence relation between (systems in) reality and the entities and relations in some scientific theory, thus consists of two jumps or interpretations: from the theory (linguistic level) to some model of it (constructural level); and from there to some system in reality. Clearly then the level of fundamental theories cannot be ignored la Nancy Cartwright - in studying the relations between a theory and reality, because the particular features of the theory (the various systems in reality onto which the theory can be mapped) cannot be studied without the underlying knowledge that these systems have one common feature, namely that each of them is the range (or other pole) of a mapping of a context-specific model of the theory - which in itself, is a mapping, or more specifically, an interpretation of the theory. I am also claiming that the nature of these levels and the relations between them necessitate an epistemological rather than an ontological notion of truth criteria, and a referential rather than a representational link between science and reality. (shrink)

To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane (J Appl Physiol 63(3):951–961, 1987 ) and introduce some dynamic properties of the respiratory system. The passive elements (rib cage and abdomen) are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles (active) force is applied to both compartments. Parameters of the model are identified in (...) using experimental data of airflow signal measured by pneumotachography and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R 2 ≥ 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing. (shrink)

In this paper, I address a question in social epistemology about the unity of a scientic community to- wards its inner groups (teams, labs...). I investigate the reasons why these groups might want to \go it alone", working among themselves and hiding their discoveries from other groups. I concentrate on the intermediate results of a longer project, where the first steps can help to achieve a more advanced result. I study to what extent the isolation of research groups might be (...) damaging to the epistemic progress of the whole community. In order to get an idea of the reason why scientists might not share their intermediate results with others, consider for example Schawlow and Townes in the summer of 1958 (the historical material is drawn from Broberg, 1991, chap. 3): together they had just designed the principle of functioning of what would be known as the laser, with the intention of constructing the rst laser, relying on their theoretical ideas. Should they have published their theoretical discovery, or rather taken advantage of their advance on possible oppo- nents and start the experimental work? They chose to publish their theoretical ideas in a scientic journal, and they also led a patent application. On the one hand, it was a valuable choice: the patent was granted and their paper was published, making them soon famous. Further- more, another scientist called Gould was to le a simi- lar patent application a few months later, in March 1959; it was refused, because of the priority of Schawlow and Townes. If the latter had not submitted their idea in 1958, the patent would certainly have been acknowl- edged to Gould. In this sense, publishing their intermediate result was a worthy strategy. On the other hand, history showed that their publication had also some drawbacks for them. Schawlow and Townes' publication triggered a race among many American laboratories for the rst experimental construction of the laser. In addition to bringing them competitors, their publication helped these competitors in crucial ways; so much so that it was another scientist, Maiman, and not Schawlow and Townes, who was able to build the rst working laser, in May 1960, and to publish the result. If Schawlow and Townes had not published their theoretical idea, there are chances that they would have been the first ones to build a laser. Their publication of the first theoretical result certainly prevented them from getting the second experimental one. In short, the best publishing strategy about an intermediate result is no easy question for a scientist. Consider now the whole community, concerned with the results available to all and with the pace of the epistemic progress. Schawlow and Townes' publication enabled the rst laser to be built quicker, as other teams could rely on their theoretical work. More generally, being able to reuse other's works seems to be a rm basis of scientic progress. Thus, for the whole community, it seems that there are only benets if intermediate results are published. As this is not necessarily the best strategy for those who reach these intermediate results, there might be a conflict between the interests of individuals and those of the whole community. The question Schawlow and Townes faced was whether they should make their discovery publicly known, or keep it for themselves to progress alone. This alternative can also arise for an entire lab, when competing with other labs on some long-run project: should it make its discoveries known to its opponents, or only share them internally among its members? At a higher level still, this question arises for what can be called scientic schools, which are groups of labs sharing some particular approach|methodological, experimental or interpre- tational, for example. At each level within the scientic community, there are competitive groups of scientists which may decide to go it alone and to prevent their results from being accessible to others. If they had good reasons for doing so, there would be dramatic consequences for the whole community: other groups would not be able to reuse their results, labour force would be wasted in achieving them again, and the progress of the eld would be slowered. 9 The aim of this paper is to investigate this risk of division: to assess the conditions under which it may oc- cur, its damage for the community, and to draw the limit of an acceptable pluralism. The reasoning with benets and drawbacks which has been sketched for Schawlow and Townes seems to be implicitly an informal economic argument. In order to clarify and to rene such an argument, I will investigate it in a rational decision framework, supposing some utility or preferences for the groups of scientists, and I will propose a formal model, in game theory. In social epistemology of science, formal models have been proposed for various questions (for example, Kitcher 1990, 1993, Goldman 2009, Strevens 2003, 2006, Weisberg and Muldoon, forthcoming, Zollman 2007, 2008, 2009, 2010), but not for the question of the division of the scientic community. I will concentrate on the normative aspect of the question, ignoring the descriptive and historical question of whether groups do go it alone or not. The model I propose is sequential: two groups are competing on a research program, which consists of several results which have to be obtained in order. The groups always carry out some research for the next result, which they reach with some probability per unit of time. When a group, say A, reaches a result, it can either make it public for the other group, or continue its research. After a result is made public, the competitor B can start from it so as to continue its own research. Thus, when A publishes it loses its lead, and its competitor will be able to compete with it in the near future. But it is also recognized as the rst to reach this step. I consider two dierent cases, one in which the number of steps is limited, another where the limit concerns the number of temporal intervals. In both cases, assuming that all steps are equally dicult and equally rewarding, it turns out that the best strategy for a group concerned with its own reward is to make public every step it takes. Thus, there is no risk that groups might separate: a scientist, whatever its group, will publish for all. Finally, I turn to more complex situations, where results have varying size or diculty: there, groups can indeed be better o going it alone. (shrink)

The aim of this paper is to re-emphasise that the purpose of formal systems is to provide something to map into and to stem the tide of unjustified formal systems. I start by arguing that expressiveness alone is not a sufficient justification for a new formal system but that it must be justified on pragmatic grounds. I then deal with a possible objection as might be raised by a pure mathematician and after that to the objection that (...) theory can be later used by more specific models. I go on to compare two different methods of developing new formal systems: by a priori principles and intuitions; and by post hoc generalisation from data and examples. I briefly describe the phenomena of “social embedding” and use it to explain the social processes that underpin “normal” and “revolutionary” science. This suggests social grounds for the popularity of normal science. I characterise the “foundational” and “empirical” approaches to the use of formal systems and situate these with respect to “normal” and “revolutionary” modes of science. I suggest that successful sciences (in the sense of developing relevant mappings to formal systems) bare either more tolerant of revolutionary ideas or this tolerance is part of the reason they are successful. I finish by enumerating a number of ‘tell-tale’ signs that a paper is presenting an unjustified formal system. (shrink)

Many weaknesses of game theory are cured by new models that embody simple cognitive principles, while maintaining the formalism and generality that makes game theory useful. Social preference models can generate team reasoning by combining reciprocation and correlated equilibrium. Models of limited iterated thinking explain data better than equilibrium models do; and they self-repair problems of implausibility and multiplicity of equilibria.

In this article, we reflect on the use of formal methods in the philosophy of science. These are taken to comprise not just methods from logic broadly conceived, but also from other formal disciplines such as probability theory, game theory, and graph theory. We explain how formal modelling in the philosophy of science can shed light on difficult problems in this domain.

This text addresses the problems of complex systems in understanding natural phenomena and the behaviour of systems related to human activity, from a science and humanities perspective. It discusses molecular behaviour and structures, and offers examples of ecological and environmental modelling.

Major figures of twentieth-century philosophy were enthralled by the revolution in formal logic, and many of their arguments are based on novel mathematical discoveries. Hilary Putnam claimed that the Löwenheim-Skølem theorem refutes the existence of an objective, observer-independent world; Bas van Fraassen claimed that arguments against empiricism in philosophy of science are ineffective against a semantic approach to scientific theories; W. V. O. Quine claimed that the distinction between analytic and synthetic truths is trivialized by the fact that (...) any theory can be reduced to one in which all truths are analytic. This book dissects these and other arguments through in-depth investigation of the mathematical facts undergirding them. It presents a systematic, mathematically rigorous account of the key notions arising from such debates, including theory, equivalence, translation, reduction, and model. The result is a far-reaching reconceptualization of the role of formal methods in answering philosophical questions. (shrink)

A cutting-edge survey of formal methods directed specifically at dealing with the deep mathematical problems engendered by the study of developing systems, in particular dealing with developing phase spaces, changing components, structures and functionalities, and the problem of emergence. Several papers deal with the modelling of particular experimental situations in population biology, economics and plant and muscle developments in addition to purely theoretical approaches. Novel approaches include differential inclusions and viability theory, growth tensors, archetypal dynamics, ensembles with variable (...) structures, and complex system models. The papers represent the work of theoreticians and experimental biologists, psychologists and economists. The areas covered embrace complex systems, the development of artificial life, mathematics, computer science, biology and psychology. (shrink)

In this book Emma Ruttkamp demonstrates the power of the full-blown employment of the model-theoretic paradigm in the philosophy of science. Within this paradigm she gives an account of sciences as process and product. She expounds the "received statement" and the "non-statement" views of science, and shows how the model-theoretic approach resolves the spurious tension between these views. In this endeavour she also engages the views of a number of contemporary philosophers of science with affinity to model (...) theory. This text can be read by specialists working in philosophy of science or formal semantics, by logicians working on the structure of theories, and by students in philosophy of science - this text offers a thorough introduction to non-statement accounts of sciences as well as a discussion of the traditional statement account of science. (shrink)

The estrangement between genetic scientists and theologians originating in the 1960s is reflected in novel combinations of human thought (subject) and genes (investigational object), paralleling each other through the universal process known in chaos theory as self-similarity. The clash and recombination of genes and knowledge captures what Philip Hefner refers to as irony, one of four voices he suggests transmit the knowledge and arguments of the religion-and-science debate. When viewed along a tangent connecting irony to leadership, journal dissemination, and (...) the activities of the "public intellectual" and the public at large, the sequence of voices is shown to resemble the passage of genetic information from DNA to mRNA, tRNA, and protein, and from cell nucleus to surrounding environment. In this light, Hefner's inquiry into the voices of Zygon is bound up with the very subject matter Zygon covers. (shrink)

Understanding nature of science is widely considered an important educational objective and views of NOS are closely linked to science teaching and learning. Thus there is a lively discussion about what understanding NOS means and how it is reached. As a result of analyses in educational, philosophical, sociological and historical research, a worldwide consensus about the content of NOS teaching is said to be reached. This consensus content is listed as a general statement of science, which students (...) are supposed to understand during their education. Unfortunately, decades of research has demonstrated that teachers and students alike do not possess an appropriate understanding of NOS, at least as far as it is defined at the general level. One reason for such failure might be that formal statements about the NOS and scientific knowledge can really be understood after having been contextualized in the actual cases. Typically NOS is studied as contextualized in the reconstructed historical case stories. When the objective is to educate scientifically and technologically literate citizens, as well as scientists of the near future, studying NOS in the contexts of contemporary science is encouraged. Such contextualizations call for revision of the characterization of NOS and the goals of teaching about NOS. As a consequence, this article gives two examples for studying NOS in the contexts of scientific practices with practicing scientists: an interview study with nanomodellers considering NOS in the context of their actual practices and a course on nature of scientific modelling for science teachers employing the same interview method as a studying method. Such scrutinization opens rarely discussed areas and viewpoints to NOS as well as aspects that practising scientists consider as important. (shrink)

The aim of cognitive neuropsychology is to articulate the functional architecture underlying normal cognition, on the basis of congnitive performance data involving brain-damaged subjects. Throughout the history of the subject, questions have been raised as to whether the methods of neuropsychology are adequate to its goals. The question has been reopened by Glymour [1994], who formulates a discovery problem for cognitive neuropsychology, in the sense of formal learning theory, concerning the existence of a reliable methodology. It appears that the (...) discovery problem may be insoluble in principle! I propose a modified formulation of Glymour's discovery problem and argue that a sceptical conclusion about the possiblity of cognitive neuropsychology as an empirical science is not warranted. (shrink)

"Habermas introduces the concept of “reconstructive science” with a double purpose: to place the “general theory of society” between philosophy and social science and reestablish the rift between the “great theorization” and the “empirical research”. The model of “rational reconstructions” represents the main thread of the surveys about the “structures” of the life-world (“culture”, “society” and “personality”) and their respective “functions” (cultural reproductions, social integrations and socialization). For this propose, the dialectics between “symbolic representation” of “the structures subordinated (...) to all worlds of life” (“internal relationships”) and the “material reproduction” of the social systems in their complex (“external relationships” between social systems and environment) has to be considered. This model finds an application, above all, in the “theory of the social evolution”, starting from the reconstruction of the necessary conditions for a phylogeny of the socio-cultural-life forms (the “hominization”) until an analysis of the development of “social formations”, which Habermas subdivides into primitive, traditional, modern and contemporary formations. This paper is an attempt, primarily, to formalize the model of “reconstruction of the logic of development” of “social formations” summed up by Habermas through the differentiation between vital world and social systems (and, within them, through the “rationalization of the life-world” and the “growth in complexity of the social systems”). Secondly, it tries to offer some methodological clarifications about the “explanation of the dynamics” of “historical processes” and, in particular, about the “theoretical meaning” of the evolutional theory’s propositions. Even if the German sociologist considers that the “ex-post rational reconstructions” and “the models system/environment” cannot have a complete “historiographical application”, these certainly act as a general premise in the argumentative structure of the “historical explanation”.". (shrink)

Recent philosophical work has praised the reward structure of science, while recent empirical work has shown that many scientific results may not be reproducible. I argue that the reward structure of science incentivizes scientists to focus on speed and impact at the expense of the reproducibility of their work, thus contributing to the so-called reproducibility crisis. I use a rational choice model to identify a set of sufficient conditions for this problem to arise, and I argue that these (...) conditions plausibly apply to a wide range of research situations. Currently proposed solutions will not fully address this problem. Philosophical commentators should temper their optimism about the reward structure of science. (shrink)

At least since Kuhn’s Structure, philosophers have studied the influence of social factors in science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social organization of science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods (...) used in science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold. (shrink)

This paper intends to further the understanding of the formal properties of (higher-order) vagueness by connecting theories of (higher-order) vagueness with more recent work in topology. First, we provide a “translation” of Bobzien's account of columnar higher-order vagueness into the logic of topological spaces. Since columnar vagueness is an essential ingredient of her solution to the Sorites paradox, a central problem of any theory of vagueness comes into contact with the modern mathematical theory of topology. Second, Rumfitt’s recent topological (...) reconstruction of Sainsbury’s theory of prototypically defined concepts is shown to lead to the same class of spaces that characterize Bobzien’s account of columnar vagueness, namely, weakly scattered spaces. Rumfitt calls these spaces polar spaces. They turn out to be closely related to Gärdenfors’ conceptual spaces, which have come to play an ever more important role in cognitive science and related disciplines. Finally, Williamson’s “logic of clarity” is explicated in terms of a generalized topology (“locology”) that can be considered an alternative to standard topology. Arguably, locology has some conceptual advantages over topology with respect to the conceptualization of a boundary and a borderline. Moreover, in Williamson’s logic of clarity, vague concepts with respect to a notion of a locologically inspired notion of a “slim boundary” are (stably) columnar. Thus, Williamson’s logic of clarity also exhibits a certain affinity for columnar vagueness. In sum, a topological perspective is useful for a conceptual elucidation and unification of central aspects of a variety of contemporary accounts of vagueness. (shrink)

Scientific research that could cause grave harm, either through accident or intentional malevolence, is known as dual-use research. Recent high-profile cases of dual-use research in the life sciences have led to debate about the extent to which restrictions on the conduct and dissemination of such research may impede scientific progress. We adapt formal models of scientific networks to systematically explore the effects that different regulatory schemes may have on a community’s ability to learn about the world. Our results suggest (...) that, contrary to common wisdom, some restrictions on the conduct and dissemination of dual-use research do not inhibit scientific progress and may actually aid communities in learning. (shrink)

This book publishes 31 of the author's selected papers which have appeared, with one exception, since 1970. The papers cover a wide range of topics in the philosophy of science. Part I is concerned with general methodology, including formal and axiomatic methods in science. Part II is concerned with causality and explanation. The papers extend the author's earlier work on a probabilistic theory of causality. The papers in Part III are concerned with probability and measurement, especially foundational (...) questions about probability. Part IV consists of several papers, including two historical ones, on the foundations of physics, with the main emphasis being on quantum mechanics. Part V, the longest part, is on the foundations of psychology and includes papers mainly on learning and perception. The book is aimed at philosophers of science, scientists concerned with the methodology of the social sciences, and mathematical psychologists interested in theories of learning, perception and measurement. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more (...) fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate (...) such topics as the nature of concepts, hypothesis formation, analogy, and theory justification. (shrink)

Hamblin distinguished between formal and descriptive dialectic. Formal normative models of deliberation dialogue have been strongly emphasized as argumentation frameworks in computer science. But making such models of deliberation applicable to real natural language examples has reached a point where the descriptive aspect needs more interdisciplinary work. The new formal and computational models of deliberation dialogue that are being built in computer science seem to be closely related to some already existing and very well established (...) computing technologies such as problem solving and decision making, but whether or how dialectical argumentation can be helpful to support these systems remains an open question. The aim of this paper is to examine some real examples of argumentation that seem to hover on the borderlines between deliberation, problem solving and decision making. (shrink)

Mazur & Booth (1998) (M&B) suggested that high testosterone (T) relates to status, dominance, and (anti-) social behaviour. However, low T also relates to status and to formal dominance. The General Trait Covariance (GTC) model predicts both relations under the assumption that high and low T modulates the genotype in ways that enforce the development of almost polar covariant patterns of body, brain, intellectual, and personality traits, irrespective of race. The precise modelling of these dose-dependent molecular body-intelligence-personality-behaviour relations (...) requires that causes, mechanisms, and effects enjoy equal operational standing. (shrink)

A comprehensive model for describing various forms of developments in science is defined in precise, set-theoretic terms, and in the spirit of the structuralist approach in the philosophy of science. The model emends previous accounts in centering on single systems in a homogenous way, eliminating notions which essentially refer to sets of systems. This is achieved by eliminating the distinction between theoretical and non-theoretical terms as a primitive, and by introducing the notion of intended links. The force of (...) the model is demonstrated by formally incorporating many of the important, precise meta-theoretic concepts occurring in the literature. (shrink)

Spinoza is most often seen as a stern advocate of mechanistic efficient causation, but examining his philosophy in relation to the Aristotelian tradition reveals this view to be misleading: some key passages of the Ethics resemble so much what Surez writes about emanation that it is most natural to situate Spinoza's theory of causation not in the context of the mechanical sciences but in that of a late scholastic doctrine of the emanative causality of the formal cause; as taking (...) a look at the seventeenth-century philosophy of mathematics reveals, this is in consonance also with Spinoza's geometrical cast of mind. Against this background, I examine Spinoza's essentialist model of causation according to which each thing has a formal character determined by the thing's essence and what follows from that essence. In the case of real things this essential causal architecture results in efficacy, i.e. in bringing about real effects, the key idea being that without the essential, formally structured causal thrust there would be no efficacy in the first place. I also explain how this model accounts for efficient causation taking place between finite things. (shrink)

An algebraic interpretation of multigraph networks is introduced in relation to conscious experience, brain and body. These multigraphs have the ability to merge by an associative binary operator \(\odot \), accounting for biological composition. We also study a mathematical formulation of splitting layers, resulting in a formal analysis of the transition from conscious to non-conscious activity. From this construction, we recover core structures for conscious experience, dynamical content and causal constraints that conscious interactions may impose. An important result is (...) the prediction of structural topological changes after conscious interactions. These results may inspire further use of formal mathematics to describe and predict new features of conscious experience while aligning well with formal tries to mathematize phenomenology, phenomenological tradition and applications to artificial consciousness. (shrink)

Contemporary debates about scientific institutions and practice feature many proposed reforms. Most of these require increased efforts from scientists. But how do scientists’ incentives for effort interact? How can scientific institutions encourage scientists to invest effort in research? We explore these questions using a game-theoretic model of publication markets. We employ a base game between authors and reviewers, before assessing some of its tendencies by means of analysis and simulations. We compare how the effort expenditures of these groups interact in (...) our model under a variety of settings, such as double-blind and open review systems. We make a number of findings, including that open review can increase the effort of authors in a range of circumstances and that these effects can manifest in a policy-relevant period of time. However, we find that open review’s impact on authors’ efforts is sensitive to the strength of several other influences. (shrink)

The transformation of the relations between reflection and reality and between concepts and their correspondent objects into themes represents even in the present a field for most heated discussions. The joining of conceptual schemes corresponding to the intellect and reality represents a problem which is still to be solved. A solution to this problem was proposed by R. Carnap in his extremely ambitious project from Der logische Aufbau der Welt (1928). Overlooked for a long time, this work has returned to (...) the philosophical spotlight in recent years, because philosophers finally realized that Carnap’s project comprises almost allthe major themes of contemporary epistemology, such as the relation between theory and reality, between concepts and experience, the major lines of a phenomenology and of a “logic of experience” or the status of language and of the concepts of science. Situated at the confluence of some philosophical traditions such as neo-kantian philosophy, the logical analysis of Russell and Wittgenstein, but also phenomenology, Carnap’s program in Aufbau starts from some premises such: the need to control experience (= major stake of any scientific knowledge); the orientation towards form of the modern concept of scientific knowledge (under Kant’s direct influence); the assertion of a concept of knowledge mostly relational or structural (issue resulted in the orientation towards form of modern knowledge); the need for a methodology engaged in a constructive way and modelled on mathematical thinking; our reporting to the instance of sensitivity in the formation of experience (under E. Mach’s influence). (shrink)

Computer models provide formal techniques that are highly relevant to philosophical issues in epistemology, metaphysics, and ethics. Such models can help philosophers to address both descriptive issues about how people do think and normative issues about how people can think better. The use of computer models in ways similar to their scientific applications substantially extends philosophical methodology beyond the techniques of thought experiments and abstract reflection. For formal philosophy, computer models offer a much broader range of representational techniques (...) than are found in traditional logic, probability, and set theory, taking into account the important roles of imagery, analogy, and emotion in human thinking. Computer models make possible investigation of the dynamics of inference, not just abstract formal relations. (shrink)