Bd. 1. Adolph Goldschmidt, Ernst Meumann, Wilhelm Waetzoldt und Arnold Schering -- Bd. 2. Paul Frankl, Emilt Utitz, Gustav Johann von Allesch und Wilhelm Worringer.

Spatial attention and eye-movements are tightly coupled, but the precise nature of this coupling is controversial. The influential but controversial Premotor theory of attention makes four specific predictions about the relationship between motor preparation and spatial attention. Firstly, spatial attention and motor preparation use the same neural substrates. Secondly, spatial attention is functionally equivalent to planning goal directed actions such as eye-movements (i.e. planning an action is both necessary and sufficient for a shift of spatial attention). Thirdly, planning a goal (...) directed action with any effector system is sufficient to trigger a shift of spatial attention. Fourthly, the eye-movement system has a privileged role in orienting visual spatial attention. This article reviews empirical studies that have tested these predictions. Contrary to predictions one and two there is evidence of anatomical and functional dissociations between endogenous spatial attention and motor preparation. However, there is compelling evidence that exogenous attention is reliant on activation of the oculomotor system. With respect to the third prediction, there is correlational evidence that spatial attention is directed to the endpoint of goal-directed actions but no direct evidence that this attention shift is dependent on motor preparation. The few studies to have directly tested the fourth prediction have produced conflicting results, so the extent to which the oculomotor system has a privileged role in spatial attention remains unclear. Overall, the evidence is not consistent with the view that spatial attention is functionally equivalent to motor preparation so the Premotor theory should be rejected, although a limited version of the Premotor theory in which only exogenous attention is dependent on motor preparation may still be tenable. A plausible alternative account is that activity in the motor system contributes to biased competition between different sensory representations with the winner of the competition becoming the attended item. (shrink)

Au cours d’une phase exploratoire, les rongeurs esquissent une forme qui oriente leur attention au contexte et assure un codage sensori-moteur des relations entre divers lieux caractéristiques selon un modèle qui s’apparente à la carte cognitive de Tolman. Selon nous, la perspective neuro-éthologique gagne en portée explicative par son articulation à la conception ruyérienne du comportement animal en soulignant le rôle de l’intégration de conduites guidées par des réponses instinctives dans l’élaboration de la cognition spatiale. Nous pouvons ainsi confronter les (...) descriptions de la neuro-éthologie à la conception ruyérienne de l’instinct « toujours thématique ». (shrink)

Models are of central importance in many scientific contexts. The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models). Scientists spend significant amounts of time building, (...) testing, comparing, and revising models, and much journal space is dedicated to interpreting and discussing the implications of models. In short, models are one of the principal instruments of modern science. (shrink)

Over the last decade the modeling and the storage of biological data has been a topic of wide interest for scientists dealing with biological and biomedical research. Currently most data is still stored in text files which leads to data redundancies and file chaos.In this paper we show how to use relational modeling techniques and relational database technology for modeling and storing biological sequence data, i.e. for data maintained in collections like EMBL or SWISS-PROT to better serve the needs for (...) these application domains. (shrink)

Over the last decade the modeling and the storage of biological data has been a topic of wide interest for scientists dealing with biological and biomedical research. Currently most data is still stored in text files which leads to data redundancies and file chaos.In this paper we show how to use relational modeling techniques and relational database technology for modeling and storing biological sequence data, i.e. for data maintained in collections like EMBL or SWISS-PROT to better serve the needs for (...) these application domains.For this reason we propose a two step approach. First, we model the structure (and therefore the meaning of the) data using an Entity-Relationship approach. The ER model leads to a clean design of a relational database schema for storing and retrieving the DNA and protein data extracted from various sources. Our approach provides the clean basis for building complex biological applications that are more amenable to changes and software ports than their file-base counterparts. (shrink)

Williams’s famous argument against immortality rests on the idea that immortality cannot be desirable, at least for human beings, and his contention has spawned a cottage industry of responses. As I will intend to show, the arguments over his view rest on both a difference of temperament and a difference in the sense of desire being used. The former concerns a difference in whether one takes a forward-looking or a backward-looking perspective on personal identity; the latter a distinction between our (...) normal desire to continue living and the kind of desire implied in desiring immortality. Showing that there is some sense of identity and desire that support Williams’s conclusion goes some way toward providing support for his argument, if not a full-fledged defense of it. (shrink)

Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the (...) representational arts. Harvard University Press, Cambridge/MA) has the resources to answer these questions. I introduce this account, outline the answers that it offers, and develop a general picture of scientific modelling based on it. (shrink)

Heidegger, like Kierkegaard, has recently been claimed as a narrativist about selves. From this Heideggerian perspective, we can see how narrative expands upon the psychological view, adding a vital teleological dimension to the understanding of selfhood while denying the reductionism implicit in the psychological approach. Yet the narrative approach also inherits the neo-Lockean emphasis on the past as determining identity, whereas the self is fundamentally about the future. Death is crucial on this picture, not as allowing for the possibility of (...) a final meaning to our lives, but as determining Dasein as ‘pure unactualizable possibility.’ Ultimately, therefore, narrative is not what constitutes selfhood – but this does not mean that narrative is not relevant to personal identity, because narrative allows identity to be expressed in action. (shrink)

Deliberation issues in decision, and so might be taken as a paradigmatic volitional activity. Character, on the other hand, may appear pre-volitional: the dispositions that constitute it provide the background against which decisions are made. Bernard Williams offers an intriguing picture of how the two may be connected via the concept of practical necessities, which are at once constitutive of character and deliverances of deliberation. Necessities are thus the glue binding character and the will, allowing us to take responsibility for (...) our characters. Intriguing though the picture may be, it did not receive a thorough elaboration in Williams’s work. My aim here is to work out and defend what I take to be the most valuable aspect of Williams’s view of agency: its model of the way character and the will can jointly determine agency through mutual constitution. However, I argue that Williams’s attempt to use this model to ground his attack on Kantian morality does not succeed, because the primacy Williams accords to character over the will cannot yield the appropriate kind of normative authority, even from the perspective of the agent. I urge that we retain Williams’s model of the interaction between character and the will, modified to allow the will an authority that is not derived from the necessity of character. (shrink)

This monograph offers a critical introduction to current theories of how scientific models represent their target systems. Representation is important because it allows scientists to study a model to discover features of reality. The authors provide a map of the conceptual landscape surrounding the issue of scientific representation, arguing that it consists of multiple intertwined problems. They provide an encyclopaedic overview of existing attempts to answer these questions, and they assess their strengths and weaknesses. The book also presents a comprehensive (...) statement of their alternative proposal, the DEKI account of representation, which they have developed over the last few years. They show how the account works in the case of material as well as non-material models; how it accommodates the use of mathematics in scientific modelling; and how it sheds light on the relation between representation in science and art. The issue of representation has generated a sizeable literature, which has been growing fast in particular over the last decade. This makes it hard for novices to get a handle on the topic because so far there is no book-length introduction that would guide them through the discussion. Likewise, researchers may require a comprehensive review that they can refer to for critical evaluations. This book meets the needs of both groups. (shrink)

Scientific discourse is rife with passages that appear to be ordinary descriptions of systems of interest in a particular discipline. Equally, the pages of textbooks and journals are filled with discussions of the properties and the behavior of those systems. Students of mechanics investigate at length the dynamical properties of a system consisting of two or three spinning spheres with homogenous mass distributions gravitationally interacting only with each other. Population biologists study the evolution of one species procreating at a constant (...) rate in an isolated ecosystem. And when studying the exchange of goods, economists consider a situation in which there are only two goods, two perfectly rational agents, no restrictions on available information, no transaction costs, no money, and dealings are done immediately. Their surface structure notwithstanding, no competent scientist would mistake descriptions of such systems as descriptions of an actual system: we know very well that there are no such systems. These descriptions are descriptions of a model-system, and scientists use model-systems to represent parts or aspects of the world they are interested in. Following common practice, I refer to those parts or aspects as target-systems. What are we to make of this? Is discourse about such models merely a picturesque and ultimately dispensable façon de parler? This was the view of some early twentieth century philosophers. Duhem (1906) famously guarded against confusing model building with scientific theorizing and argued that model building has no real place in science, beyond a minor heuristic role. The aim of science was, instead, to construct theories, with theories understood as classificatory or representative structures systematically presented and formulated in precise symbolic.. (shrink)

In this paper we explore the constraints that our preferred account of scientific representation places on the ontology of scientific models. Pace the Direct Representation view associated with Arnon Levy and Adam Toon we argue that scientific models should be thought of as imagined systems, and clarify the relationship between imagination and representation.

It is now part and parcel of the official philosophical wisdom that models are essential to the acquisition and organisation of scientific knowledge. It is also generally accepted that most models represent their target systems in one way or another. But what does it mean for a model to represent its target system? I begin by introducing three conundrums that a theory of scientific representation has to come to terms with and then address the question of whether the semantic view (...) of theories, which is the currently most widely accepted account of theories and models, provides us with adequate answers to these questions. After having argued in some detail that it does not, I conclude by pointing out in what direction a tenable account of scientific representation might be sought. (shrink)

Everything you always wanted to know about structural realism but were afraid to ask Content Type Journal Article Pages 227-276 DOI 10.1007/s13194-011-0025-7 Authors Roman Frigg, Department of Philosophy, Logic and Scientific Method, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE UK Ioannis Votsis, Philosophisches Institut, Heinrich-Heine-Universität Düsseldorf, Universitätsstraße 1, Geb. 23.21/04.86, 40225 Düsseldorf, Germany Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number (...) 2. (shrink)

Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science , but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of (...) models and theories, and the relation between experimentation and theorising, and submit that simulations demand a fundamentally new philosophy of science in many respects. The aim of this paper is to critically evaluate these claims. Our conclusion will be sober. We argue that these claims are overblown and that simulations, far from demanding a new metaphysics, epistemology, semantics and methodology, raise few if any new philosophical problems. The philosophical problems that do come up in connection with simulations are not specific to simulations and most of them are variants of problems that have been discussed in other contexts before. (shrink)

Science provides us with representations of atoms, elementary particles, polymers, populations, genetic trees, economies, rational decisions, aeroplanes, earthquakes, forest fires, irrigation systems, and the world’s climate. It's through these representations that we learn about the world. This entry explores various different accounts of scientific representation, with a particular focus on how scientific models represent their target systems. As philosophers of science are increasingly acknowledging the importance, if not the primacy, of scientific models as representational units of science, it's important to (...) stress that how they represent plays a fundamental role in how we are to answer other questions in the philosophy of science. This entry begins by disentangling ‘the’ problem of scientific representation, before critically evaluating the current options available in the literature. (shrink)

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we challenge (...) the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement. (shrink)

Our reply to Fabian Freyenhagen’s article “Was ist orthodoxe Kritische Theorie?” (DZPhil 65.3 [2017], 456-469) raises the question whether his proposal that Critical Theory only “be adequately and appropriately critical” without a program of justification spares the search for any general criteria. Answering negatively we conversely want to recall, particularly with regard to Horkheimers’s and Adornos’s Dialectic of Enlightment as well as Habermas‘s concept of an emancipatory interest, that such a criterion as a normative foundation of critique is crucial not (...) only for systematical purposes, but also recognised as necessary in this respect by Adorno, who Freyenhagen wants to play off against programs of justification. Critical Theory needs to be clear in this respect. Against this background we are questioning Freyenhagen‘s recourse to an “interest in abolishing social injustice” as the “only criterion for Critical Theory.” Because Freyenhagen ignores the fact that Critical Theory has been understood by its representatives in a twofold manner – as a theoretical program of justification for one and secondly as a cultural diagnosis – his plea for an orthodox Critical Theory is endangered by decisionism. (shrink)

Classical statistical mechanics posits probabilities for various events to occur, and these probabilities seem to be objective chances. This does not seem to sit well with the fact that the theory’s time evolution is deterministic. We argue that the tension between the two is only apparent. We present a theory of Humean objective chance and show that chances thus understood are compatible with underlying determinism and provide an interpretation of the probabilities we find in Boltzmannian statistical mechanics.

This is an extensive review of recent work on the foundations of statistical mechanics.