Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a case study empirical research on the alleged empirical association between (...) human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call tendential prediction. (shrink)

_ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a (...) case study empirical research on the alleged empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call _tendential prediction_. (shrink)

In aesthetics, the topic of intentions comes up most often in the perennial debate between intentionalists and anti-intentionalists over standards of interpretation. The underlying assumptions about the nature and functions of intentions are, however, rarely explicitly developed, even though divergent and at times tendentious premises are often relied upon in this controversy. Livingston provides a survey of contentions about the nature and status of intentions and intentionalist psychology more generally, arguing for an account that recognizes the multiple functions fulfilled by (...) intentions in the lives of temporally situated agents who deliberate over what to do, settle on ends and means, and try to realize some of their plans. Artists’ intentions are the same sorts of attitudes that we attribute to ourselves and to others as we attempt to describe, explain, and predict our actions. As such, intentions are relevant not only to debates over the interpretation of works of art but also to a range of other basic topics in the philosophy of art, including artistic creation and authorship, the ontology of art, the nature of texts, works, versions, and life-works, and the status and nature of fiction and fictional truth. With regard to the controversy over the interpretation of art, Livingston advocates a ‘partial’ intentionalism. Intentions are never infallible, so there is a conceptual gap between the completed work and the intentions that initiated and guided its making. Yet in spite of the fallibility of intentions and of our beliefs and claims about them, intentions regularly contribute to the determination of a work’s features, including implicit meanings, the recognition of which requires the uptake of the artist’s intentional design. Partial intentionalism also finds support in the idea that at least one sort of artistic value depends on the artist’s skilful accomplishment of intentions. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:American Journal of Philology 124.3 (2003) 477-481 [Access article in PDF] Martha C. Nussbaum and Juha Sihvola, eds. The Sleep of Reason: Erotic Experience and Sexual Ethics in Ancient Greece and Rome. Chicago: University of Chicago Press, 2002. viii + 457 pp. Paper, $26. The Sleep of Reason derives from a conference held at the Finnish Institute at Rome in 1997. In their introduction to the volume, the editors, (...) Martha Nussbaum and Juha Sihvola, note that the incommensurability between sexual behavior/desire and reason was a perennial concern to ancient philosophers and that the modern discipline of philosophy has avoided this topic because of skittishness about "emotional topics" (3) and a pronounced tendency to consider ancient philosophy in a decontextualized manner. The editors accordingly have assembled a mixture of papers on ancient philosophy and other aspects of ancient culture to bring philosophical rigor and context to discussions of ancient sexual ethics. With only a third of the papers specifically about philosophy, however, the volume is more "context" than philosophy. Of greater concern, however, is their claim that the book covers both Greece and Rome. With the exception of Cantarella's discussion of Roman marriage law, Konstan's of Catullus, and Goldhill's few pages on Tertullian, substantive discussion of Latin sources is lacking. The book treats classical Greece in some detail and then skips through Greek sources to the Second Sophistic. Indeed, the failure to engage imperial Rome substantively leaves Goldhill's essay damagingly decontextualized. The editors' tendentious sketch of modern scholarship on ancient sexual behavior (7-8), which overlooks important contributions of Eva Keuls and Amy Richlin, is likewise regrettable.In the first paper, "Forgetting Foucault: Acts, Identities, and the History of Sexuality," David Halperin prescribes a proper way to investigate ancient sexual activity. Beginning with a discussion of Michel Foucault's famous statement on the progress from sodomy ("a category of forbidden acts") to the homosexual ("a life form... a species"), Halperin persuasively argues that Foucault's statement has been misunderstood as social history when it is better regarded "as a claim about the internal logic and systematic functioning of two different discursive styles of sexual disqualification" (28). Elsewhere, however, Halperin's disciplining zeal is wearisome. Opposing the terms deviant sexual morphology and deviant sexual subjectivity (the former deviance in gender presentation and the latter identity based on sexual activity), Halperin predictably asserts that the cinaedus possessed a deviant sexual morphology whose non-normative sexual behavior sprang from innate effeminacy. According to ideology recoverable from the sources, this is correct. Consideration of the cinaedus latens (from Firmicus [End Page 477] Maternus; see below), to take an example, brings up a question: what are we to make of this cinaedus if "the kinaidos's betrayal of his masculine gender identity was so spectacular as to brand him a deviant type of person and to inscribe his deviant identity all over his face and body" (34)? Caution is called for here; discourse surely produces less schematic results (see, e.g., Foucault, The History of Sexuality, Vol. 1 [1978], 96, or Judith Butler, GenderTrouble [1990], 28).In "Eros and Ethical Norms: Philosophers Respond to a Cultural Dilemma," Nussbaum surveys different approaches to the uneasy coexistence of sexual desire and education in pederastic relationships: if Eros is about loss of control in the face of desire, will the ero \ menos be cared for properly or merely be the means for desire's satisfaction? Nussbaum compares Socrates' explication of a "generous madness," wherein reverence and gratitude inspire kindly care, to the Stoics' valuation of friendship undertaken with consummate self-control. Nussbaum's work here has considerable value in its explication of the Stoic position and in her conclusion on the usefulness of analysis of ancient philosophic responses to ero \ s in current debates about sexuality (86-87).The next two papers, Maarit Kaimio's "Erotic Experience in the Conjugal Bed: Good Wives in Greek Tragedy" and Stephen Halliwell's "Aristophanic Sex: The Erotics of Shamelessness," take us to the Athenian stage. Starting from the observation that words for "bed"... (shrink)

Without needing to commit to any specific claims about what states of affairs have most agent-neutral value, we can nevertheless predict that states of affairs which are relatively valuable are also relatively likely to occur—on the grounds that, all else equal, at least some other agents are likely to recognize the value of those states of affairs, pursue them because they are valuable, and successfully bring them about as a consequence of that pursuit. This gives us a way to promote (...) value as such, rather than promoting it under some more tendentious description. We can predict that actions which help other people—or our own future selves—to recognize valuable states of affairs, actions which motivate them to pursue whatever states of affairs they believe to be valuable, or actions which help them succeed at their pursuits will, all else equal, have positive consequences. So we have a pro tanto reason to take such actions, and the subjective justification of that reason is independent of other moral claims. (shrink)

How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...) be prediction machines - devices that have evolved to anticipate the incoming streams of sensory stimulation before they arrive. These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation. (shrink)

In his paper, Jakob Hohwy outlines a theory of the brain as an organ for prediction-error minimization, which he claims has the potential to profoundly alter our understanding of mind and cognition. One manner in which our understanding of the mind is altered, according to PEM, stems from the neurocentric conception of the mind that falls out of the framework, which portrays the mind as “inferentially-secluded” from its environment. This in turn leads Hohwy to reject certain theses of embodied (...) cognition. Focusing on this aspect of Hohwy’s argument, we first outline the key components of the PEM framework such as the “evidentiary boundary,” before looking at why this leads Hohwy to reject certain theses of embodied cognition. We will argue that although Hohwy may be correct to reject specific theses of embodied cognition, others are in fact implied by the PEM framework and may contribute to its development. We present the metaphor of the “body as a laboratory” in order to highlight wha... (shrink)

According to the thesis of Strong Predictionism, we typically have stronger evidence for a theory if it was used to predict certain data, than if it was deliberately constructed to accommodate those same data, even if we fully grasp the theory and all the evidence on which it was based. This thesis faces powerful objections and the existing arguments in support of it are seriously flawed. I offer a new defence of Strong Predictionism which overcomes the objections and provides a (...) deeper understanding of the epistemic importance of prediction. I conclude by applying this account to strategies for defending scientific realism. (shrink)

The Recursive Bayesian Net (RBN) formalism was originally developed for modelling nested causal relationships. In this paper we argue that the formalism can also be applied to modelling the hierarchical structure of mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations is vital for prediction, explanation and control respectively, an RBN can be applied to all these tasks. We show in (...) particular how a simple two-level RBN can be used to model a mechanism in cancer science. The higher level of our model contains variables at the clinical level, while the lower level maps the structure of the cell's mechanism for apoptosis. (shrink)

COVID-19 has substantially affected our lives during 2020. Since its beginning, several epidemiological models have been developed to investigate the specific dynamics of the disease. Early COVID-19 epidemiological models were purely statistical, based on a curve-fitting approach, and did not include causal knowledge about the disease. Yet, these models had predictive capacity; thus they were used to ground important political decisions, in virtue of the understanding of the dynamics of the pandemic that they offered. This raises a philosophical question about (...) how purely statistical models can yield understanding, and if so, what the relationship between prediction and understanding in these models is. Drawing on the model that was developed by the Institute of Health Metrics and Evaluation, we argue that early epidemiological models yielded a modality of understanding that we call descriptive understanding, which contrasts with the so-called explanatory understanding which is assumed to be the main form of scientific understanding. We spell out the exact details of how descriptive understanding works, and efficiently yields understanding of the phenomena. Finally, we vindicate the necessity of studying other modalities of understanding that go beyond the conventionally assumed explanatory understanding. (shrink)

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...) dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%. (shrink)

According to the so-called ‘deliberation crowds out prediction’ thesis, while deliberating about what you’ll do, you cannot rationally have credences for what you’ll do – you cannot rationally have option-credences. Versions of the thesis have been defended by authors such as Spohn, Levi, Gilboa, Price, Louise, and others. After registering a number of concerns about the thesis, I rehearse and rebut many of the main arguments for it, grouped according to their main themes: agency, vacuity, betting, and decision-theoretical considerations. (...) I go on to suggest many possible theoretical roles for option-credences. -/- I locate the debate about the thesis in a broader discussion: Are there rational credence gaps – propositions to which one cannot rationally assign credences? If there are, they spell trouble for various foundations of Bayesian epistemology, including the usual ratio formula for conditional probability, conditionalization, decision theory, and independence. According to the thesis, credence gaps are completely mundane; they arise every time someone rationally deliberates. But these foundations are safe from any threat here, I contend, since the thesis is false. Deliberation welcomes prediction. (shrink)

Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors in identifying (...) PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%. (shrink)

This book develops a philosophico-methodological analysis of prediction and its role in economics. Prediction plays a key role in economics in various ways. It can be seen as a basic science, as an applied science, and in the application of this science. First, it is used by economic theory in order to test the available knowledge. In this regard, prediction has been presented as the scientific test for economics as a science. Second, prediction provides a content (...) regarding the possible future that can be used for prescription in applied economics. Thus, it can be used as a guide for economic policy, id est, as knowledge concerning the future to be employed for the resolution of specific problems. Third, prediction also has a role in the application of this science in the public arena. This is through the decision-making of the agents - individuals or organizations - in quite different settings, both in the realm of microeconomics and macroeconomics. Within this context, the research is organized in five parts, which discuss relevant aspects of the role of prediction in economics: I) The problem of prediction as a test for a science; II) The general orientation in methodology of science and the problem of prediction as a scientific test; III) The methodological framework of social sciences and economics: Incidence for prediction as a test; IV) Epistemology and methodology of economic prediction: Rationality and empirical approaches; and V) Methodological aspects of economic prediction: From description to prescription. Thus, the book is of interest for philosophers and economists as well as policy-makers seeking to ascertain the roots of their performance. The style used lends itself to a wide audience.. (shrink)

From ‘connecting the dots’ and finding ‘the needle in the haystack’ to predictive policing and data mining for counterinsurgency, security professionals have increasingly adopted the language and methods of computing for the purposes of prediction. Digital devices and big data appear to offer answers to a wide array of problems of (in)security by promising insights into unknown futures. This article investigates the transformation of prediction today by placing it within governmental apparatuses of discipline, biopower and big data. Unlike (...) disciplinary and biopolitical governmentality, we argue that prediction with big data is underpinned by the production of a different time/space of ‘between-ness’. The digital mode of prediction with big data reconfigures how we are governed today, which we illustrate through an analysis of how predictive policing actualizes between-ness as hotspots and near-real-time decisions. (shrink)

Short-term traffic flow prediction is an effective means for intelligent transportation system to mitigate traffic congestion. However, traffic flow data with temporal features and periodic characteristics are vulnerable to weather effects, making short-term traffic flow prediction a challenging issue. However, the existing models do not consider the influence of weather changes on traffic flow, leading to poor performance under some extreme conditions. In view of the rich features of traffic data and the characteristic of being vulnerable to external (...) weather conditions, the prediction model based on traffic data has certain limitations, so it is necessary to conduct research studies on traffic flow prediction driven by both the traffic data and weather data. This paper proposes a combined framework of stacked autoencoder and radial basis function neural network to predict traffic flow, which can effectively capture the temporal correlation and periodicity of traffic flow data and disturbance of weather factors. Firstly, SAE is used to process the traffic flow data in multiple time slices to acquire a preliminary prediction. Then, RBF is used to capture the relation between weather disturbance and periodicity of traffic flow so as to gain another prediction. Finally, another RBF is used for the fusion of the above two predictions on decision level, obtaining a reconstructed prediction with higher accuracy. The effectiveness and robustness of the proposed model are verified by experiments. (shrink)

Recommender systems are recently developed computer-assisted tools that support social and informational needs of various communities and help users exploit huge amounts of data for making optimal decisions. In this study, we present a new recommender system for assessment and risk prediction in child welfare institutions in Israel. The system exploits a large diachronic repository of manually completed questionnaires on functioning of welfare institutions and proposes two different rule-based computational models. The system accepts users’ requests via a simple graphical (...) interface, calculates the institutions’ profiles according to user preferences, and presents assessment scores, trends and comparative analyses of the corresponding data using assorted visual aids. Based on the analysis, the system offers three different strategies for objective assessment of the institutions’ functioning and risks. Qualitative and quantitative evaluation of the system’s effectiveness and accuracy demonstrates that it substantially improves the assessment process of a welfare institution. Moreover, it provides an effective tool for objective large-scale analysis of the institution’s overall state and trends, which were previously based primarily on the institution supervisors’ subjective judgment and intuition. In addition, the proposed recommender system has great practical and social impact as it may help identify and avert potential problems, malfunctions, flaws, risks and even tragic incidents in child welfare institutions, as well as increase their overall functioning levels. As a result, as a long-term social implication, the system may also help reduce inequality and social gaps in the Israeli society. (shrink)

Alan Hájek launches a formidable attack on the idea that deliberation crowds out prediction – that when we are deliberating about what to do, we cannot rationally accommodate evidence about what we are likely to do. Although Hájek rightly diagnoses the problems with some of the arguments for the view, his treatment falls short in crucial ways. In particular, he fails to consider the most plausible version of the view, the best argument for it, and why anyone would ever (...) believe it in the first place. In doing so, he misses a deep puzzle about deliberation and prediction – a puzzle which all of us, as agents, face, and which we may be able to resolve by recognizing the complicated relationship between deliberation and prediction. (shrink)

For multiple reasons, deliberating groups often converge on falsehood rather than truth. Individual errors may be amplifi ed rather than cured. Group members may fall victim to a bad cascade, either informational or reputational. Deliberators may emphasize shared information at the expense of uniquely held information. Finally, group polarization may lead even rational people to unjustifi ed extremism. By contrast, prediction markets often produce accurate results, because they create strong incentives for revelation of privately held knowledge and succeed in (...) aggregating widely dispersed information. The success of prediction markets off ers a set of lessons for increasing the likelihood that groups can obtain the information that their members have. (shrink)

Hans Reichenbach was a formidable figure in early-twentieth-century philosophy of science. Educated in Germany, he was influential in establishing the so-called Berlin Circle, a companion group to the Vienna Circle founded by his colleague Rudolph Carnap. The movement they founded—usually known as "logical positivism," although it is more precisely known as "scientific philosophy" or "logical empiricism"—was a form of epistemology that privileged scientific over metaphysical truths. Reichenbach, like other young philosophers of the exact sciences of his generation, was deeply impressed (...) by the far-reaching changes in physics brought about by Einstein's special and general theories of relativity. Reichenbach responded to scientific advances by doing fundamental work in space-time theories, in quantum mechanics, in statistical mechanics, and in the development of probability theory—making him the most important philosopher of physics in the first generation of logical empiricism. Forced from his academic position by the Nazi race laws in 1933, Reichenbach wrote _Experience and Prediction_ at the University of Istanbul, where had had fled, expressly to introduce logical positivism to English speakers. In the two decades following World War II, during the explosion of scientific advances in North America, logical positivism was the reigning theory of the philosophy of science and Reichenbach was at the peak of his career. But, inevitably, support for logical positivism began to wane as it became obvious that the justification of scientific theories could not be entirely resolved by relying on strictly formal, technical processes. The growth of the discipline of the history of philosophy of science, which has created an audience of scholars eager for seminal classics in scientific philosophy, and the evidence supporting a historicist paradigm within logical positivism are two important reasons to make _Experience and Prediction_ available once again. "Hans Reichenbach's_ Experience and Prediction_ is one of the most important books in twentieth-century philosophy of science. Its author was, along with Rudolf Carnap, one of the two principal ambassadors to North America of the exciting new European philosophical movement known here under the names 'Logical Positivism' and 'Scientific Philosophy.' In 1938, when the book was published, Reichenbach was an exile from his native Germany, teaching in Istanbul, Turkey, and about to emigrate to the United States to take up a prestigious position at UCLA. He wrote_ Experience and Prediction_ in English as his calling card to his new American colleagues. More than any other single book,_ Experience and Prediction_ set the agenda for the new discipline of the philosophy of science that was to emerge after World War II as, perhaps, the most exciting new area in North American philosophy. Many of the problems still at the focus of discussion were given their classic formulations in this book. Long out of print,_ Experience and Prediction_ appears here in a new edition accompanied by a splendid historical introduction by the noted young philosopher and historian of the philosophy of science, Alan Richardson. A jewel of a book may once again be appreciated in its proper setting." —Don A. Howard, University of Notre Dame. (shrink)

Courtesy of its free energy formulation, the hierarchical predictive processing theory of the brain (PTB) is often claimed to be a grand unifying theory. To test this claim, we examine a central case: activity of mesocorticolimbic dopaminergic (DA) systems. After reviewing the three most prominent hypotheses of DA activity—the anhedonia, incentive salience, and reward prediction error hypotheses—we conclude that the evidence currently vindicates explanatory pluralism. This vindication implies that the grand unifying claims of advocates of PTB are unwarranted. More (...) generally, we suggest that the form of scientific progress in the cognitive sciences is unlikely to be a single overarching grand unifying theory. (shrink)

In their theoretical and experimental reflections on the capacities and behaviours of living systems, neuroscientists often formulate generalizations about the behaviour of neural circuits. These generalizations are highly idealized, as they omit reference to the myriads of conditions that could perturb the behaviour of the modelled system in real-world settings. This article analyses an experimental investigation of the behaviour of place cells in the rat hippocampus, in which highly idealized generalizations were tested by comparing predictions flowing from them with real-world (...) experimental results. The aim of the article is to identify under what conditions even single prediction failures regarding the behaviour of single cells sufficed to reject highly idealized generalizations, and under what conditions prima facie counter-examples were deemed to be irrelevant to the testing of highly idealized generalizations. The results of this analysis may contribute to understanding how idealized models are tested experimentally in neuroscience and used to make reliable predictions concerning living systems in real-world settings. (shrink)

Branding is a magic weapon for enterprises to participate in international competition, and empowering enterprises through branding has become a national strategy in the new era. Economic and social development has won wide acclaim from the international community, but enterprises generally have the problem of being “big but not strong”, which is not matching with long history and great power influence. The brand bottleneck of Chinese enterprises has been highlighted. Recent brand theory research has been fruitful on the whole, but (...) there are also some weak links, among which “the mechanism of enterprise brand value formation” is a research theme to be strengthened. This paper presents a number of suggestions for the formation of corporate brand value. The empirical analysis was conducted using valid data. The results found that: customer involvement behavior has a significant positive influence on customer citizenship behavior and customer experience value. Customer experience value has a significant positive influence on customer satisfaction and customer commitment. It plays a mediating effect in the relationship between the influence of customer involvement behavior on customer satisfaction and customer commitment, respectively. Customer satisfaction has a significant positive influence on customer commitment, and plays a mediating customer commitment has a significant positive effect on customer citizenship behavior and mediates the effect of customer experience value on customer citizenship behavior. The experimental results show that: the accuracy of crop color recognition by this method is high, and it has the advantages of faster computational efficiency and higher computational accuracy compared with other algorithms, thus verifying the reliability of the algorithm. Based on the fuzzy sentiment of online reviews, this paper improves the continuous use model ECM-ISC and formulates the inference rules of fuzzy affiliation function, and verifies the brand conversion intention and brand conversion type of cell phones by example calculation, which has good accuracy and generality and has important practical significance for brand marketing and early warning management. In addition, the use of brand economics in the study of corporate brand positioning is a development and innovation of brand economics. (shrink)

In the past two decades, reinforcement learning has become a popular framework for understanding brain function. A key component of RL models, prediction error, has been associated with neural signals throughout the brain, including subcortical nuclei, primary sensory cortices, and prefrontal cortex. Depending on the location in which activity is observed, the functional interpretation of prediction error may change: Prediction errors may reflect a discrepancy in the anticipated and actual value of reward, a signal indicating the salience (...) or novelty of a stimulus, and many other interpretations. Anterior cingulate cortex has long been recognized as a region involved in processing behavioral error, and recent computational models of the region have expanded this interpretation to include a more general role for the region in predicting likely events, broadly construed, and signaling deviations between expected and observed events. Ongoing modeling work investigating the interaction between ACC and additional regions involved in cognitive control suggests an even broader role for cingulate in computing a hierarchically structured surprise signal critical for learning models of the environment. The result is a predictive coding model of the frontal lobes, suggesting that predictive coding may be a unifying computational principle across the neocortex. (shrink)

In this paper I reconstruct and critically examine the reasoning leading to the famous prediction of the ‘omega minus’ particle by M. Gell-Mann and Y. Ne’eman (in 1962) on the basis of a symmetry classification scheme. While the peculiarity of this prediction has occasionally been noticed in the literature, a detailed treatment of the methodological problems it poses has not been offered yet. By spelling out the characteristics of this type of prediction, I aim to underscore the (...) challenges raised by this episode to standard scientific methodology, especially to the traditional deductive-nomological account of prediction. (shrink)

The universal optimality theorem for metainduction works for epistemic agents faced with a choice among finitely many prediction methods. Eckhart Arnold and Tom Sterkenburg objected that it breaks...

Textor’s The Disappearance of the Soul and the Turn Against Metaphysics examines the voluntarist background of Schlick’s epistemology, including his conception of knowledge as essentially involving judgements that relate at least two terms, and his connected objection against according intuition epistemic status. Textor interprets Schlick’s conception of intuition in light of Schopenhauer’s distinction between ordinary and extra-ordinary cognition. Thus Textor argues that Schlick takes intuition to be a form of ‘steady contemplation’ (Disappearance, 348) of an object that is ‘either a (...) universal or a particular’ (332). I suggest an alternative interpretation, according to which Schlick takes intuition to be an immersion into the contents of the stream of consciousness, which he claims to be a formless ‘Heraclitian flux’ (General Theory, 31, 156). This interpretation allows for a defence, against Textor’s objections, of Schlick’s thesis that the aim of knowledge is prediction. If the kind of flux given in pure intuition is genuinely ‘Heraclitian’ – that is to say, if the stream of consciousness is ever-changing and unrepeatable – then it is simply impossible for ‘the devotee of intuition’ (150) to predict its course. By contrast, the process of re-cognition that constitutes knowledge is intimately tied to prediction. (shrink)

Climate models don’t give us probabilistic forecasts. To interpret their results, alternatively, as serious possibilities seems problematic inasmuch as climate models rely on contrary-to-fact assumptions: why should we consider their implications as possible if their assumptions are known to be false? The paper explores a way to address this possibilistic challenge. It introduces the concepts of a perfect and of an imperfect credible world, and discusses whether climate models can be interpreted as imperfect credible worlds. That would allow one to (...) use models for possibilistic prediction and salvage widespread scientific practice. (shrink)

The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close relationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in inference can be obtained by means of the so-called statistical distance between probability distributions. When applied to quantum mechanics, this distance leads to a measure of the distinguishability of quantum states, which essentially is the absolute value of (...) the matrix element between the states. The importance of this result to the quantum mechanical uncertainty principle is noted. The second part of the paper provides a derivation of the statistical distance on the basis of the so-called method of support. (shrink)

Every model leaves out or distorts some factors that are causally connected to its target phenomenon -- the phenomenon that it seeks to predict or explain. If we want to make predictions, and we want to base decisions on those predictions, what is it safe to omit or to simplify, and what ought a causal model to describe fully and correctly? A schematic answer: the factors that matter are those that make a difference to the target phenomenon. There are several (...) ways to understand differencemaking. This paper advances a view as to which is the most relevant to the forecaster and the decision-maker. It turns out that the right notion of differencemaking for thinking about idealization in prediction is also the right notion for thinking about idealization in explanation; this suggests a carefully circumscribed version of Hempel's famous thesis that there is a symmetry between explanation and prediction. (shrink)

Research on human causal learning has largely focused on strength learning, or on computational-level theories; there are few formal algorithmic models of how people learn causal structure from covariations. We introduce a model that learns causal structure in a local manner via prediction-error learning. This local learning is then integrated dynamically into a unified representation of causal structure. The model uses computationally plausible approximations of rational learning, and so represents a hybrid between the associationist and rational paradigms in causal (...) learning research. We conclude by showing that the model provides a good fit to data from a previous experiment. (shrink)

A not unpopular thesis, when it comes to the confirmation of scientific theories, is that data which were used in the construction of a theory afford poorer support for that theory than data that played no role. Some compelling thought experiments have been offered in favour of this view, not as proof but rather to add some intuitive plausibility. In this paper I consider such thought experiments and argue that they do not support the thesis; the perceived importance of (...) class='Hi'>prediction over accommodation, at least in these cases, is illusory. Introduction Background assumptions Strong thesis Weak thesis Conclusions. (shrink)

We observe that approaches to intersubjectivity, involving mirror neurons and involving emulation and prediction, have eclipsed discussion of those same mechanisms for achieving coordination between the two hemispheres of the human brain. We explore some of the implications of the suggestion that the mutual modelling of the two situated hemispheres is a productive place to start in understanding the phylogenetic and ontogenetic development of cognition and of intersubjectivity.