In his paper “Whatever next? Predictive brains, situated agents, and the future of cognitive science,” Andy Clark seminally proposed that the brain's job is to predict whatever information is coming “next” on the basis of prior inputs and experiences. Perception fundamentally subserves survival and self-preservation in biological agents, such as humans. Survival however crucially depends on rapid and accurate information processing of what is happening in the here and now. Hence, the term “next” in Clark's seminal formulation must include (...) not only the temporal dimension (i.e., what is perceivednow) but also the spatial dimension (i.e., what is perceivedhereor next-to-my-body). In this paper, we propose to focus on perceptual experiences that happen “next,” i.e., close-to-my-body. This is because perceptual processing of proximal sensory inputs has a key impact on the organism's survival. Specifically, we focus on tactile experiences mediated by the skin and what we will call the “extended skin” or “second skin,” that is, immediate objects/materials that envelop closely to our skin, namely, clothes. We propose that the skin and tactile experiences are not a mere border separating the self and world. Rather, they simultaneously and inherently distinguishandconnect the bodily self to its environment. Hence, these proximal and pervasive tactile experiences can be viewed as a “transparent bridge” intrinsically relating and facilitating exchanges between the self and the physical and social world. We conclude with potential implications of this observation for the case of Depersonalization Disorder, a condition that makes people feel estranged and detached from their self, body, and the world. (shrink)

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind (...) is that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. (shrink)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of (...) sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (shrink)

Real-world policy decisions involve trade-offs. Sometimes the trade-offs involve both the efficacy and morality of potential policies. In this chapter, the morality and likely efficacy of hiring one more spy to help anti-terrorist intelligence gathering efforts is compared to the morality and likely efficacy of implementing a prediction market on terrorism. Prediction markets on terrorism allow registered traders to buy and sell shares in predictions about terrorism-related real-world events. The comparison at the heart of this chapter is based on the (...) assumption that it would cost about $5 million to bankroll the prediction market project, or to establish another spy, including equipment and head office support, for 15 years. The comparison reveals that implementing a prediction market on terrorism is likely to be more efficacious and less morally problematic than hiring one more spy. (shrink)

In this paper, we compare and contrast institutional theory and convention theory on the concept of mimetism, suggesting how they can cross-pollinate each other and more specifically how the self-referential quality of collective beliefs improves the understanding of mimetic isomorphism. We test this proposition with the case of responsible investment’s mainstreaming.First level results decompose the history of RI into five successive periods. A content analysis of articles on RI in the financial press leads to second level results consisting in a (...) number of salient representations of RI, which we consider to be the dominant conventions. The data is structured using a bracketing strategy, which allows a longitudinal analysis of conventions and their evolution over the five RI periods. (shrink)

El autor realiza una lectura de las Enéadas de Plotino partiendo de la noción de procesión, pieza clave para comprender la arquitectura del universo plotiniana ordenado jerárquicamente alrededor del Uno-Bien.Del primer principio proceden todos los seres y en él convergen. Cuatro son fundamentalmente los aspectos tratados: 1) El axiomade la procesión. 2) Los dos momentos de la procesión: el ascendente y el descendente. 3) Las imágenes de la procesión.4) Dentro de estas metáforas, privilegia el centro y el círculo, núcleo en (...) el análisis de la noción de procesión. (shrink)

Ghosn, Mariam Predictive genetic testing Part 2 will examine the issues and ethical aspects that must be considered when adolescents below the age of majority make a request to undergo predictive genetic testing for Huntington's disease.

Social scientists increasingly use social media data to illuminate long-standing substantive questions in social science research. However, a key challenge of analyzing such data is their lower level of individual detail compared to highly detailed survey data. This limits the scope of substantive questions that can be addressed with these data. In this study, we provide a method to upgrade individual detail in terms of ethnicity in data gathered from social media via the use of register data. Our research aim (...) is twofold: first, we predict the most likely value of ethnicity, given one's first name, and second, we show how one can test hypotheses with the predicted values for ethnicity as an independent variable while simultaneously accounting for the uncertainty in these predictions. We apply our method to social network data collected from Facebook. We illustrate our approach and provide an example of hypothesis testing using our procedure, i.e., estimating the relation between predicted network ethnic homogeneity on Facebook and trust in institutions. In a comparison of our method with two other methods, we find that our method provides the most conservative tests of hypotheses. We discuss the promise of our approach and pinpoint future research directions. (shrink)

The development of Information and Communication Technologies has favored access to technological resources in adolescents. These tools provide access to information that can promote learning. However, they can also have a negative effect against people, as they can be used with other functionality, in which cyberbullying situations are caused during the interactions that arise when using social networks. The objective of this study was to determine the predictive value of the role of cyberbullying victims based on variables related to (...) other roles involved in cyberbullying and bullying, as well as personal characteristics, contextual characteristics and positive teamwork habits.. Information was collected from 227 students of the educational stages of Primary Education and Secondary Education, aged between 11 and 15 years, in a city with a high index of cultural diversity. The step-by-step technique was used to build the regression model. The results indicate that the model has a good goodness of fit coefficient. The role of cyberbully is the most important predictive variable of the role of the victim in cyberbullying and, to a lesser extent, the role of the witness in cyberbullying, the role of the witness in bullying, and the role of the victim of bullying. The role of the bullying aggressor and the variables sex, age, type of educational center, and teamwork habits are excluded in the predictive model. (shrink)

Drawing on recent findings in the cognitive and neurosciences, this article discusses how people manage to predict each other’s actions, which is fundamental for joint action. We explore how a common coding of perceived and performed actions may allow actors to predict the what, when, and where of others’ actions. The “what” aspect refers to predictions about the kind of action the other will perform and to the intention that drives the action. The “when” aspect is critical for all joint (...) actions requiring close temporal coordination. The “where” aspect is important for the online coordination of actions because actors need to effectively distribute a common space. We argue that although common coding of perceived and performed actions alone is not sufficient to enable one to engage in joint action, it provides a representational platform for integrating the actions of self and other. The final part of the paper considers links between lower‐level processes like action simulation and higher‐level processes like verbal communication and mental state attribution that have previously been at the focus of joint action research. (shrink)

This study aimed to investigate the common predictive factors between social media addiction and eating disorder symptoms, in a group of Chinese female college students. A total of 216 students completed the behavioral assessments of cognitive flexibility and sustained attention, as well as the questionnaires on anxiety, social media dependence, and eating disorders. The results indicate that SMA is significantly correlated with EDS. Structural equation modeling was used to test the model in which state anxiety, cognitive flexibility, and sustained (...) attention predicted social gain and EDS. Additionally, the results confirmed the mediating role of cognitive flexibility and sustained attention between state anxiety and SMA/EDS in the participants. The findings revealed that in the sample group, state anxiety was related to SMA and EDS through cognitive flexibility and sustained attention. These proposals reflect the significance of improving cognitive flexibility/sustained attention and reducing state anxiety to prevent EDS and SMA in female college students. (shrink)

The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and academics (...) have begun to raise critical questions about the use of these tools in policing contexts. In this chapter, I review the emerging critical literature on predictive policing and contribute to it by raising ethical questions about the use of predictive analytics tools to identify potential offenders. Drawing from work on the ethics of profiling, I argue that the much-lauded move from reactive to preemptive policing can mean wrongfully generalizing about individuals, making harmful assumptions about them, instrumentalizing them, and failing to respect them as full ethical persons. I suggest that these problems stem both from the nature of predictive policing tools and from the sociotechnical contexts in which they are implemented... (shrink)

This chapter seeks to recover an approach to consciousness from a general theory of brain function, namely the prediction error minimization theory. The way this theory applies to mental and developmental disorder demonstrates its relevance to consciousness. The resulting view is discussed in relation to a contemporary theory of consciousness, namely the idea that conscious perception depends on Bayesian metacognition; this theory is also supported by considerations of psychopathology. This Bayesian theory is first disconnected from the higher-order thought theory, and (...) then, via a prediction error conception of action, connected instead to the global neuronal workspace theory. Considerations of mental and developmental disorder therefore show that a very general theory of brain function is relevant to explaining the structure of conscious perception; furthermore, this theory can subsume and unify two contemporary approaches to consciousness, in a move that seeks to elucidate the fundamental mechanism for selection of representational content into consciousness. (shrink)

The predictive processing literature contains at least two different versions of the framework with different theoretical resources at their disposal. One version appeals to so-called optimistic priors to explain agents’ motivation to act (call this optimistic predictive processing). A more recent version appeals to expected free energy minimization to explain how agents can decide between different action policies (call this preference predictive processing). The difference between the two versions has not been properly appreciated, and they are not (...) sufficiently separated in the literature. They constitute two different theories with strikingly different accounts of motivation and action. By reducing all desire-like constructs to belief-like constructs, optimistic predictive processing entails a substantial revision of standard accounts of motivation and action in philosophy and cognitive science. By contrast, preference predictive processing introduces desire-like constructs that play Humean motivational roles in the explanation of action. In this Humean iteration, predictive processing resembles other prominent computational frameworks implementing a distinction between beliefs and desires, such as reinforcement learning and Bayesian decision theory. Ultimately, predictive processing faces a dilemma between parsimony of mental constructs and completeness of its explanations of agency and the mind. (shrink)

In tennis, service requires a variety of complicated movements. Given the importance of taking the initiative to obtain points in a tennis match, it is crucial to make full use of speed and spin rate of service. Generally, a service that requires a higher spin rate would slow down, and a service that has increased speed would have a decreased spin rate. For players who are disadvantaged in height, although controlling spin rate is essential, slowing down service speed should be (...) avoided. For these players, the challenge of service is to improve the speed without decreasing the spin rate. Players must also be trained to build physical strength required for this skill. It is not uncommon to work on physical training without a racket; however, few studies have reported on the effects of cultivated physical strength on on-court tennis performance. Therefore, this study aimed to propose physical measurements that could be used as indices to improve service performance in 58 elite Japanese junior male players. To test service performance, we used TrackMan tennis radar device to assess speed, spin rate, impact height, and impact depth. To test physical strength, we measured 5- and 20-m sprint, broad jump, medicine ball throw. We used a significant multiple regression equation to predict the first service speed obtained from the broad jump and the Medicine ball throw. Additionally, a strong correlation was obtained between the predicted and measured values. In addition to physical strength, we suggest that the depth of the impact point is important for improving the first service speed. However, we were not able to identify the physical strength test items that improve service spin rate. Other item should be examined in the future to determine the physical strength associated with spin rate. This result could help connect physical training and service performance. (shrink)

Current diagnostic criteria for schizophrenia place emphasis on delusions and hallucinations, whereas the classical descriptions of schizophrenia by Kraepelin and Bleuler emphasized disorganization and impoverishment of mental activity. Despite the availability of antipsychotic medication for treating delusions and hallucinations, many patients continue to experience persisting disability. Improving treatment requires a better understanding of the processes leading to persisting disability. We recently introduced the term classical schizophrenia to describe cases with disorganized and impoverished mental activity, cognitive impairment and predisposition to persisting (...) disability. Recent evidence reveals that a polygenic score indicating risk for schizophrenia predicts severity of the features of classical schizophrenia: disorganization, and to a lesser extent, impoverishment of mental activity and cognitive impairment. Current understanding of brain function attributes a cardinal role to predictive coding: the process of generating models of the world that are successively updated in light of confirmation or contradiction by subsequent sensory information. It has been proposed that abnormalities of these predictive processes account for delusions and hallucinations. Here we examine the evidence provided by electrophysiology and fMRI indicating that imprecise predictive coding is the core pathological process in classical schizophrenia, accounting for disorganization, psychomotor poverty and cognitive impairment. Functional imaging reveals aberrant brain activity at network hubs engaged during encoding of predictions. We discuss the possibility that frequent prediction errors might promote excess release of the neurotransmitter, dopamine, thereby accounting for the occurrence of episodes of florid psychotic symptoms including delusions and hallucinations in classical schizophrenia. While the predictive coding hypotheses partially accounts for the time-course of classical schizophrenia, the overall body of evidence indicates that environmental factors also contribute. We discuss the evidence that chronic inflammation is a mechanism that might link diverse genetic and environmental etiological factors, and contribute to the proposed imprecision of predictive coding. (shrink)

In this study, the focus was on the development of green energy and future prediction for the consumption of current energy sources and green energy development using an improved deep learning algorithm. In addition to the analysis of the current energy consumption used for the natural gas and oil as fuel, deep neural network algorithm is used to train the system as well as to process the data obtained previously, ranging from literature from the year 2003 until the year 2019, (...) for consumption of fuel. Also, using the proposed algorithm to predict the development of green energy consumption till 2030 is presented in terms of solar and wind generators. The resulting study also focuses on depletion of energy currently used or pollution caused because of it. The green energy controlling issue can take effect by using multiple layers of handling different features extracted from different sources and then learning the system to control it.This study aims to take advantage of carbon emissions to reduce their impact and dependence in the future on environmentally friendly renewable energies. Predicting the correct and precise amount of energy consumption and increasing the amount of environmentally friendly energy lead to a healthy ecosystem. The expected green energy consumption in the future is almost 78.25 EJ in 2030 and will be, in total energy average, 56% in 2045. The aim is to reduce dependency on costly and environmentally harmful fuels. (shrink)

an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the (...) key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments. (shrink)

Are predictions about how one will freely and intentionally behave in the future ever relevant to how one ought to behave? There is good reason to think they are. As imperfect agents, we have responsibilities of self-management, which seem to require that we take account of the predictable ways we're liable to go wrong. I defend this conclusion against certain objections to the effect that incorporating predictions concerning one's voluntary conduct into one's practical reasoning amounts to evading responsibility for that (...) conduct. There is, however, some truth to this sort of objection. To understand the legitimate role of self-prediction in practical reasoning, we need to distinguish instances of coping responsibly with an anticipated failure to behave as one ought, on the one hand, from mere acquiescence in one's flaws, on the other. I argue that, to draw this distinction, we must recognize certain limits on the use of self-prediction as a ground of choice. (shrink)

Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to (...) predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%. (shrink)

This paper examines the relationship between perceiving and imagining on the basis of predictive processing models in neuroscience. Contrary to the received view in philosophy of mind, which holds that perceiving and imagining are essentially distinct, these models depict perceiving and imagining as deeply unified and overlapping. It is argued that there are two mutually exclusive implications of taking perception and imagination to be fundamentally unified. The view defended is what I dub the ecological–enactive view given that it does (...) not succumb to internalism about the mind-world relation, and allows one to keep a version of the received view in play. (shrink)

An analytic cognitive style denotes a propensity to set aside highly salient intuitions when engaging in problem solving. We assess the hypothesis that an analytic cognitive style is associated with a history of questioning, altering, and rejecting supernatural claims, both religious and paranormal. In two studies, we examined associations of God beliefs, religious engagement, conventional religious beliefs and paranormal beliefs with performance measures of cognitive ability and analytic cognitive style. An analytic cognitive style negatively predicted both religious and paranormal beliefs (...) when controlling for cognitive ability as well as religious engagement, sex, age, political ideology, and education. Participants more willing to engage in analytic reasoning were less likely to endorse supernatural beliefs. Further, an association between analytic cognitive style and religious engagement was mediated by religious beliefs, suggesting that an analytic cognitive style negatively affects religious engagement via lower acceptance of conventional religious beliefs. Results for types of God belief indicate that the association between an analytic cognitive style and God beliefs is more nuanced than mere acceptance and rejection, but also includes adopting less conventional God beliefs, such as Pantheism or Deism. Our data are consistent with the idea that two people who share the same cognitive ability, education, political ideology, sex, age and level of religious engagement can acquire very different sets of beliefs about the world if they differ in their propensity to think analytically. (shrink)

Nature Connection (NC) is considered an important driver of conservation behavior. Consequently, conservation organizations run many activities aiming to increase NC among participants. However, little is known about which activities are most effective at doing this and why. This study developed the Evaluating Nature Activities for Connection Tool (ENACT), to evaluate the effectiveness of activities for increasing participants’ NC and nature-related intentions. ENACT comprises 11 activity aspects identified through two research phases. In Phase 1, a literature search, focus group and (...) interviews identified desired, short-term behavioral outcomes of nature activities, and variables that might promote these. In Phase 2, 241 adults completed a pilot survey immediately post-nature activity, with 1-month follow-up (N= 145), to evaluate the impact of participation on NC, nature-related behavioral intentions and behaviors. ENACT correlated with NC measures and offered incremental validity in predicting nature-related behavioral intentions and self-reported behaviors after 1 month. (shrink)

A major disagreement between different views about the foundations of quantum mechanics concerns whether for a theory to be intelligible as a fundamental physical theory it must involve a ‘primitive ontology’ (PO), i.e. variables describing the distribution of matter in four-dimensional space–time. In this article, we illustrate the value of having a PO. We do so by focusing on the role that the PO plays for extracting predictions from a given theory and discuss valid and invalid derivations of predictions. To (...) this end, we investigate a number of examples based on toy models built from the elements of familiar interpretations of quantum theory. (shrink)

A widely endorsed thesis in the philosophy of science holds that if evidence for a hypothesis was not known when the hypothesis was proposed, then that evidence confirms the hypothesis more strongly than would otherwise be the case. The thesis has been thought to be inconsistent with Bayesian confirmation theory, but the arguments offered for that view are fallacious. This paper shows how the special value of prediction can in fact be given Bayesian explanation. The explanation involves consideration of the (...) reliability of the method by which the hypothesis was discovered, and thus reveals an intimate connection between the 'logic of discovery' and confirmation theory. (shrink)

I propose an account of the speech act of prediction that denies that the contents of prediction must be about the future and illuminates the relation between prediction and assertion. My account is a synthesis of two ideas: (i) that what is in the future in prediction is the time of discovery and (ii) that, as Benton and Turri recently argued, prediction is best characterized in terms of its constitutive norms.

Seepage analysis is always a concern in dam safety and stability research. The prediction and analysis of seepage pressure monitoring data is an effective way to ensure the safety and stability of dam seepage. With the timeliness of a change in a monitoring value and lag due to external influences, a RS-LSTM model written in Python is developed in this paper which combines rough set theory and the long- and short-term memory network model. The model proposed calculates the prediction score (...) of the seepage pressure of a dam experiencing multiple effects by preordering factor importance values to eliminate the interference of redundant factors. A case study shows that the water level, rainfall, temperature, and duration are all factors that affect the seepage pressure, and their importance values decrease successively. Thus, the seepage pressure of a dam can be predicted with a determination coefficient R2 of 0.96. Compared with the recurrent neural network model and BP neural network model, the training time of the RS-LSTM model proposed is 6.37 s, and the operation efficiency is 41% and 59% higher than that of the RNN and BP models, respectively. The mean relative error is also 3.00%, which is 50% lower than that of the RNN model and 31% lower than that of the BP model. Based on these results, this model has the advantages of fast computation speed and high accuracy in prediction. (shrink)

Recent work in computational and cognitive neuroscience depicts the brain as an ever‐active prediction machine: an inner engine continuously striving to anticipate the incoming sensory barrage. I briefly introduce this class of models before contrasting two ways of understanding the implied vision of mind. One way (Conservative Predictive Processing) depicts the predictive mind as an insulated inner arena populated by representations so rich and reconstructive as to enable the organism to ‘throw away the world’. The other (Radical (...) class='Hi'>Predictive Processing) stresses the use of fast and frugal, action‐involving solutions of the kind highlighted by much work in robotics and embodied cognition. But it goes further, by showing how predictive schemes can combine frugal and more knowledge‐intensive strategies, switching between them fluently and continuously as task and context dictate. I end by exploring some parallels with work in enactivism, and by noting a certain ambivalence concerning internal representations and their role in the predictive mind. (shrink)

Predictive Processing theory, hotly debated in neuroscience, psychology and philosophy, promises to explain a number of perceptual and cognitive phenomena in a simple and elegant manner. In some of its versions, the theory is ambitiously advertised as a new theory of conscious perception. The task of this paper is to assess whether this claim is realistic. We will be arguing that the Predictive Processing theory cannot explain the transition from unconscious to conscious perception in its proprietary terms. The (...) explanations offer by PP theorists mostly concern the preconditions of conscious perception, leaving the genuine material substrate of consciousness untouched. (shrink)

Twitter is a virtual social network where people share their posts and opinions about the current situation, such as the coronavirus pandemic. It is considered the most significant streaming data source for machine learning research in terms of analysis, prediction, knowledge extraction, and opinions. Sentiment analysis is a text analysis method that has gained further significance due to social networks’ emergence. Therefore, this paper introduces a real-time system for sentiment prediction on Twitter streaming data for tweets about the coronavirus pandemic. (...) The proposed system aims to find the optimal machine learning model that obtains the best performance for coronavirus sentiment analysis prediction and then uses it in real-time. The proposed system has been developed into two components: developing an offline sentiment analysis and modeling an online prediction pipeline. The system has two components: the offline and the online components. For the offline component of the system, the historical tweets’ dataset was collected in duration 23/01/2020 and 01/06/2020 and filtered by #COVID-19 and #Coronavirus hashtags. Two feature extraction methods of textual data analysis were used, n-gram and TF-ID, to extract the dataset’s essential features, collected using coronavirus hashtags. Then, five regular machine learning algorithms were performed and compared: decision tree, logistic regression, k-nearest neighbors, random forest, and support vector machine to select the best model for the online prediction component. The online prediction pipeline was developed using Twitter Streaming API, Apache Kafka, and Apache Spark. The experimental results indicate that the RF model using the unigram feature extraction method has achieved the best performance, and it is used for sentiment prediction on Twitter streaming data for coronavirus. (shrink)

1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.

In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in hospitals. The evaluation (...) of testing the dataset shows that the ANN model is capable of correctly predicting the birth weight with 100% accuracy. (shrink)

This paper and its predecessor () are about the question: 'Are the events in the entire universe encoded in and predictable from any of its parts?' To approach a positive answer in classical physics, the following result is proved and commented on: in Newton's theory of gravitation, the entire trajectory of a particle can be predicted given any segment of it, regardless of how the other particles are moving-provided that there is only a finite number of particles and that their (...) speeds remain bounded. (It is this condition, together with a set of parameters characterising the motion of the other particles, which enables us to estimate the effect of the other particles on the trajectory of the given particle.) The extension of this result to other theories, in particular to special relativity, is discussed. (shrink)

Predictive processing (PP) accounts of perception are unique not merely in that they postulate a unity between perception and imagination. Rather, they are unique in claiming that perception should be conceptualised in terms of imagination and that the two involve an identity of neural implementation. This paper argues against this postulated unity, on both conceptual and empirical grounds. Conceptually, the manner in which PP theorists link perception and imagination belies an impoverished account of imagery as cloistered from the external (...) world in its intentionality, akin to a virtual reality, as well as endogenously generated. Yet this ignores a whole class of imagery whose intentionality is directed on the actual environment—projected mental imagery—and also ignores the fact that imagery may be triggered crossmodally in a bottom-up, stimulus-driven way. Empirically, claiming that imagery and perception share neural circuitry ignores relevant clinical results in this area. These evidence substantial perception/imagery neural dissociations, most notably in the case of aphantasia. Taken together, the arguments here suggest that PP theorists should substantially temper, if not outright abandon, their claim to a perception/imagination unity. (shrink)

Although prediction has been largely absent from discussions of explanation for the past 40 years, theories of explanation can gain much from a reintroduction. I review the history that divorced prediction from explanation, examine the proliferation of models of explanation that followed, and argue that accounts of explanation have been impoverished by the neglect of prediction. Instead of a revival of the symmetry thesis, I suggest that explanation should be understood as a cognitive tool that assists us in generating new (...) predictions. This view of explanation and prediction clarifies what makes an explanation scientific and why inference to the best explanation makes sense in science. *Received August 2009; revised September 2009. †To contact the author, please write to: Department of Philosophy, University of Tennessee, 801 McClung Tower, Knoxville, TN 37920‐0480; e‐mail: [email protected]. (shrink)

In order to solve the problem of unsmooth and inefficient human-computer interaction process in the information age, a method for human-computer interaction intention prediction based on electroencephalograph signals and eye movement signals is proposed. This approach is different from previous methods where researchers predict using data from human-computer interaction and a single physiological signal. This method uses the eye movements and EEG signals that clearly characterized the interaction intention as the prediction basis. In addition, this approach is not only tested (...) with multiple human-computer interaction intentions, but also takes into account the operator in different cognitive states. The experimental results show that this method has some advantages over the methods proposed by other researchers. In Experiment 1, using the eye movement signal fixation point abscissa Position X, fixation point ordinate Position Y, and saccade amplitude to judge the interaction intention, the accuracy reached 92%, In experiment 2, only relying on the pupil diameter, pupil size and fixed time, fixed time of eye movement signals can not achieve higher accuracy of the operator’s cognitive state, so EEG signals are added. The cognitive state was identified separately by combining the screened EEG parameters Rα/β with the eye movement signal pupil diameter and fixation time, with an accuracy of 91.67%. The experimental combination of eye movement and EEG signal features can be used to predict the operator’s interaction intention and cognitive state. (shrink)

In the methodology of scientific research programs (MSRP) there are important features on the problem of prediction, especially regarding novel facts. In his approach, Imre Lakatos proposed three different levels on prediction: aim, process, and assessment. Chapter 5 pays attention to the characterization of prediction in the methodology of research programs. Thus, it takes into account several features: (1) its pragmatic characterization, (2) the logical perspective as a proposition, (3) the epistemological component, (4) its role in the appraisal of research (...) programs, and (5) its place as a value for scientific research. -/- The notion of “novel facts” is highly relevant in his conception, where several aspects are involved: the directions of novel facts, the different kinds of novelty, and the transition from six possible options of “novel facts” to four choices. Thereafter, the prediction of novel facts as the criterion of appraisal is considered. On the one hand, this requires analyzing the theoretical, empirical, and heuristic possibilities of appraisal; and, on the other, whether there is an overemphasis on the role of prediction in methodology of scientific research programs. As a consequence, there is an analysis of Lakatos’ criterion of appraisal in MSRP and economics. (shrink)

The predictive inadequacy of the social sciences is well documented, and philosophers have sought to diagnose it. This paper examines Brian Epstein’s recent diagnosis. He argues that the social sciences treat the social world as entirely composed of individual people. Instead, social scientists should recognize that material, non-individualistic entities determine the social world, as well. First, I argue that Epstein’s argument both begs the question against his opponents and is not sufficiently charitable. Second, I present doubts that his proposal (...) will improve predictive success for the social sciences, which I support with Edith Penrose’s resource-based theory of the firm. (shrink)

Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role of orthodox (...) economic theory. Second, a conditional predictivism: if we are not committed to orthodox economic theory, then we should demand prediction rather than accommodation – against most current practice. (shrink)

Predictive processing, an increasingly popular paradigm in cognitive sciences, has focused primarily on giving accounts of perception, motor control and a host of psychological phenomena, including consciousness. But higher cognitive processes, like conceptual thought, language, and logic, have received only limited attention to date and PP still stands disconnected from a huge body of research in those areas. In this thesis, I aim to address this gap and I attempt to go some way towards developing and defending a cognitive-computational (...) approach to higher cognition within the predictive processing paradigm. To test its explanatory potential, I apply it to a range of linguistic and conceptual phenomena. I proceed in three steps. First, I lay out an account of concepts and suggest how concepts are represented, how they can be context-sensitively processed, and how the apparent diversity of formats arise. Secondly, I propose how paradigmatic higher cognitive competencies, like language and logical reasoning, could fit into the PP picture. Thirdly, I apply the PP account of concepts and language to a range of linguistic-conceptual phenomena as test cases, namely: metaphor, the semantic paradox (specifically the Liar Paradox) and copredication. Finally, I discuss some challenges and objections to the PP framework as applied to higher cognition and in general. (shrink)