The aim of this article is to shed light on Kant’s anthropological theory of memory. I shall contrast physiological studies of memory against Kant’s own study. I suggest some ideas about the relation between memory and time, as long as memory has the power to store and reproduce the temporal configuration of our representations. Moreover, I deal with the problem of personal identity and I suggest that memory contributes to the possibility of this identity from a pragmatic point of view. (...) Finally, I hold that Kant’s pragmatic anthropology does not only provide a description of memory for the human being’s self-knowledge but also for the human being’s self-perfection. Thus, such description discloses not only what the human being is but also what this can become, insofar as it is capable of perfecting itself. (shrink)

This paper analyses the features of Kant’s view of memory, which Kant himself described explicitly in his lectures on anthropology and implicitly in the A edition of the Critique of Pure Reason. I shall offer a review of literature on Kant’s view of memory up to this day. I suggest that memory is a cognitive faculty that has the power to store and reproduce representations. Kant distinguishes among three different kinds of memorization which are relevant for human cognition. I offer (...) reasons to hold that imagination and memory must be differentiated by their functioning, although the first one grounds the second one. Finally, I hold that certain functions of memory need to be presupposed at a transcendental level, in which memory would play a fundamental function with regard to the possibility of experience. Resumen Este artículo analiza los rasgos de la concepción de la memoria de Kant, los cuales él describió explícitamente en sus lecciones sobre antropología e implícitamente en la edición A de la Crítica de la Razón Pura. Proporcionaré una revisión de la literatura sobre la concepción de Kant acerca de la memoria hasta el presente. Sugiero que la memoria es una facultad cognitiva que tiene el poder de almacenar y reproducir representaciones. Kant distingue tres tipos diferentes de memorización, los cuales son relevantes para el conocimiento humano. Asimismo, proporciono razones para sostener que la imaginación y la memoria deben ser diferenciadas por su funcionamiento, aunque la primera es el fundamento de la segunda. Finalmente, sostengo que ciertas funciones de la memoria necesitan ser presupuestas a un nivel trascendental, en el cual la memoria cumpliría una función fundamental con respecto a la posibilidad de la experiencia. (shrink)

Nowadays, batteries play an important role in a lot of different applications like energy storage, electro-mobility, consumer electronic and so on. All the battery types have a common factor that is their complexity, independently of its nature. Usually, the batteries have an electrochemical nature. Several different test are accomplished to check the batteries performance, and commonly, it is predictable how they work depending of their technology. The present research describes the hybrid intelligent system created to accomplish fault detection over a (...) Lithium Iron Phosphate—LiFePO4 power cell type, commonly used in electro-mobility applications. The approach is based on the cell temperatures behaviour for voltage and current specific values. Taken into account the operating range of a real system based on a LiFePO4 cell, a large set of points of operation have been used to achieve the dataset. The different behaviour zones have been obtained by clustering as a first step. Then, different regression techniques have been used over each cluster. Polynomial regression, artificial neural networks and support vector regression were the combined techniques to develop the hybrid intelligent model proposed. The intelligent system gives very good results over the operating range, detecting all the faults tested during the validation. (shrink)

The Internet of Things (IoT) is a fast-growing technology that connects everyday devices to the Internet, enabling wireless, low-consumption and low-cost communication and data exchange. IoT has revolutionized the way devices interact with each other and the internet. The more devices become connected, the greater the risk of security breaches. There is currently a need for new approaches to algorithms that can detect malware regardless of the size of the network and that can adapt to dynamic changes in the network. (...) Through the use of a multi-agent reinforcement learning algorithm, this paper proposes a novel algorithm for malware detection in IoT devices. The proposed algorithm is not strongly dependent on the size of the IoT network due to the that its training is adapted using time differences if the IoT network size is small or Monte Carlo otherwise. To validate the proposed algorithm in an environment as close to reality as possible, we proposed a scenario based on a real IoT network, where we tested different malware propagation models. Different simulations varying the number of agents and nodes in the IoT network have been developed. The result of these simulations proves the efficiency and adaptability of the proposed algorithm in detecting malware, regardless of the malware propagation model. (shrink)

Batteries are a fundamental storage component due to its various applications in mobility, renewable energies and consumer electronics among others. Regardless of the battery typology, one key variable from a user’s perspective is the remaining energy in the battery. It is usually presented as the percentage of remaining energy compared to the total energy that can be stored and is labeled State Of Charge (SOC). This work addresses the development of a hybrid model based on a Lithium Iron Phosphate (LiFePO4) (...) power cell, due to its broad implementation. The proposed model calculates the SOC, by means of voltage and electric current as inputs and the latter as the output. Therefore, four models based on k-Means, Agglomerative Clustering, Gaussian Mixture and Spectral Clustering techniques have been tested in order to obtain an optimal solution. (shrink)

This paper aims to enhance security in IoT device networks through a visual tool that utilizes three projection techniques, including Beta Hebbian Learning (BHL), t-distributed Stochastic Neighbor Embedding (t-SNE) and ISOMAP, in order to facilitate the identification of network attacks by human experts. This work research begins with the creation of a testing environment with IoT devices and web clients, simulating attacks over Message Queuing Telemetry Transport (MQTT) for recording all relevant traffic information. The unsupervised algorithms chosen provide a set (...) of projections that enable human experts to visually identify most attacks in real-time, making it a powerful tool that can be implemented in IoT environments easily. (shrink)

Detecting intrusions in large networks is a highly demanding task. In order to reduce the computation demand of analysing every single packet travelling along one of such networks, some years ago flows were proposed as a way of summarizing traffic information. Very few research works have addressed intrusion detection in flows from a visualizations perspective. In order to bridge this gap, the present paper proposes the application of a novel projection method (Beta Hebbian Learning) under this framework. With the aim (...) to validate this method, 8 traffic segments, containing many flows, have been analysed by means of this projection method. The promising results obtained for these segments, extracted from the University of Twente dataset, validate the proposed application. (shrink)

The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems can (...) be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results. (shrink)

In this contribution, we use the connection between stable polynomials and orthogonal polynomials on the real line to construct sequences of Hurwitz polynomials that are robustly stable in terms of several uncertain parameters. These sequences are constructed by using properties of orthogonal polynomials, such as the well-known three-term recurrence relation, as well as by considering linear combinations of two orthogonal polynomials with consecutive degree. Some examples are presented.

Present research proposes the application of unsupervised and supervised machine-learning techniques to characterize Android malware families. More precisely, a novel unsupervised neural-projection method for dimensionality-reduction, namely, Beta Hebbian Learning, is applied to visually analyze such malware. Additionally, well-known supervised Decision Trees are also applied for the first time in order to improve characterization of such families and compare the original features that are identified as the most important ones. The proposed techniques are validated when facing real-life Android malware data by (...) means of the well-known and publicly available Malgenome dataset. Obtained results support the proposed approach, confirming the validity of BHL and DTs to gain deep knowledge on Android malware. (shrink)

A hemi-implicative lattice is an algebra \((A,\wedge,\vee,\rightarrow,1)\) of type (2, 2, 2, 0) such that \((A,\wedge,\vee,1)\) is a lattice with top and for every \(a,b\in A\), \(a\rightarrow a = 1\) and \(a\wedge (a\rightarrow b) \le b\). A new variety of hemi-implicative lattices, here named sub-Hilbert lattices, containing both the variety generated by the \(\{\wedge,\vee,\rightarrow,1\}\) -reducts of subresiduated lattices and that of Hilbert lattices as proper subvarieties is defined. It is shown that any sub-Hilbert lattice is determined (up to isomorphism) by (...) a triple (_L_, _D_, _S_) which satisfies the following conditions: _L_ is a bounded distributive lattice, _D_ is a sublattice of _L_ containing 0, 1 such that for each \(a, b \in L\) there is an element \(c \in D\) with the property that for all \(d \in D\), \(a \wedge d \le b\) if and only if \(d \le c\) (we write \(a \rightarrow _D b\) for the element _c_), and _S_ is a non void subset of _L_ such that _S_ is closed under \(\rightarrow _D\) and _S_, with its inherited order, is itself a lattice. Finally, the congruences of sub-Hilbert lattices are studied. (shrink)

In this research work a novel two-step system for anomaly detection is presented and tested over several real datasets. In the first step the novel Exploratory Projection Pursuit, Beta Hebbian Learning algorithm, is applied over each dataset, either to reduce the dimensionality of the original dataset or to face nonlinear datasets by generating a new subspace of the original dataset with lower, or even higher, dimensionality selecting the right activation function. Finally, in the second step Principal Component Analysis anomaly detection (...) is applied to the new subspace to detect the anomalies and improve its classification capabilities. This new approach has been tested over several different real datasets, in terms of number of variables, number of samples and number of anomalies. In almost all cases, the novel approach obtained better results in terms of area under the curve with similar standard deviation values. In case of computational cost, this improvement is only remarkable when complexity of the dataset in terms of number of variables is high. (shrink)

Nowadays, the quality standards of higher education institutions pay special attention to the performance and evaluation of the students. Then, having a complete academic record of each student, such as number of attempts, average grade and so on, plays a key role. In this context, the existence of missing data, which can happen for different reasons, leads to affect adversely interesting future analysis. Therefore, the use of imputation techniques is presented as a helpful tool to estimate the value of missing (...) data. This work deals with the academic records of engineering students, in which imputation techniques are applied. More specifically, it is assessed and compared to the performance of the multivariate imputation by chained equations methodology, the adaptive assignation algorithm based on multivariate adaptive regression splines and a hybridization based on self-organisation maps with Mahalanobis distances and AAA algorithm. The results show that proposed methods obtain successfully results regardless the number of missing values, in general terms. (shrink)

The use of batteries became essential in our daily life in electronic devices, electric vehicles and energy storage systems in general terms. As they play a key role in many devices, their design and implementation must follow a thorough test process to check their features at different operating points. In this circumstance, the appearance of any kind of deviation from the expected operation must be detected. This research deals with real data registered during the testing phase of a lithium iron (...) phosphate—LiFePO4—battery. The process is divided into four different working points, alternating charging, discharging and resting periods. This work proposes a hybrid classifier, based on one-class techniques, whose aim is to detect anomalous situations during the battery test. The faults are created by modifying the measured cell temperature a slight ratio from their real value. A detailed analysis of each technique performance is presented. The average performance of the chosen classifier presents successful results. (shrink)

A large part of technological advances, especially in the field of industry, have been focused on the optimization of productive processes. However, the detection of anomalies has turned out to be a great challenge in fields like industry, medicine or stock markets. The present work addresses anomaly detection on a control level plant. We propose the application of different intelligent techniques, which allow to obtain one-class classifiers using real data taken from the correct plant operation. The performance of each classifier (...) is assessed and validated with real created faults, achieving successful overall results. (shrink)

In this study, a hybrid model based on intelligent techniques is developed to predict the active power generated in a bioclimatic house by a low power wind turbine. Contrary to other researches that predict the generated power taking into account the speed and the direction of the wind, the model developed in this paper only uses the speed of the wind, measured mainly in a weather station from the government meteorological agency (MeteoGalicia). The wind speed is measured at different heights, (...) against the usual measurements in others researches, which uses the wind speed and the direction measured in a weather station on the wind turbine nacelle. The prediction is performed 30 minutes ahead, what ensures that the Building Management System knows the energy generated by the low power wind turbine 30 minutes before, and it can adapt the consumption of different equipment in the house to optimize the power use. The main objective is to allow the Building Management System to optimize the uses of energy, taking into account the predicted amount of energy that will be produced and the energy consumed in the house. The developed model uses a hybrid topology with four clusters to improve the prediction, achieving an error lower than 6.5% for Mean Absolute Error measured in a final test. To perform this test, part of the original dataset was isolated from the beginning of the training process to check the model with a dataset that is not used before, simulating the model as it is receiving new data. (shrink)

The concept of polarity is pervasive in natural language. It relates syntax, semantics and pragmatics narrowly, Semantics: an international handbook of natural language meaning, De Gruyter Mouton, Berlin, 2011; Israel in The grammar of polarity: pragmatics, sensitivity, and the logic of scales, Cambridge studies in linguistics, Cambridge University Press, Cambridge, 2014), it refers to items of many syntactic categories such as nouns, verbs and adverbs. Neutral polarity items appear in affirmative and negative sentences, negative polarity items cannot appear in affirmative (...) sentences, and positive polarity items cannot appear in negative sentences. A way of reasoning in Natural Language is through Natural Logic. This logic is based on the concept of polarity in order to make the meaning of a sentence weaker o stronger without changing its truth value. There exist many proposals to compute polarity in the Natural Logic context, the most widely known are the ones by: van Benthem, Sánchez-Valencia, Dowty, and van Eijck, 6th international Tbilisi symposium on logic, language, and computation, Batumi, Georgia, Springer, 2007). If Natural Logic is going to be used, as an inferential mechanism between text fragments, in Natural Language Processing applications such as text summarization, question answering, and information extraction, it is a priority to know what the existing relationship among the aforementioned algorithms is; for example, to implement the most general. We show in this paper the equivalence among the analyzed algorithms, filling a gap in Natural Logic research, particularly in computing polarity, and the soundness of their algorithms. (shrink)

The Internet of Things (IoT) presents a unique cybersecurity challenge due to its vast network of interconnected, resource-constrained devices. These vulnerabilities not only threaten data integrity but also the overall functionality of IoT systems. This study addresses these challenges by exploring efficient data reduction techniques within a model-based intrusion detection system (IDS) for IoT environments. Specifically, the study explores the efficacy of an autoencoder’s latent space combined with three different classification techniques. Utilizing a validated IoT dataset, particularly focusing on the (...) Constrained Application Protocol (CoAP), the study seeks to develop a robust model capable of identifying security breaches targeting this protocol. The research culminates in a comprehensive evaluation, presenting encouraging results that demonstrate the effectiveness of the proposed methodologies in strengthening IoT cybersecurity with more than a 99% of precision using only 2 learned features. (shrink)

Closed-loop administration of propofol for the control of hypnosis in anesthesia has evidenced an outperformance when comparing it with manual administration in terms of drug consumption and post-operative recovery of patients. Unlike other systems, the success of this strategy lies on the availability of a feedback variable capable of quantifying the current hypnotic state of the patient. However, the appearance of anomalies during the anesthetic process may result in inaccurate actions of the automatic controller. These anomalies may come from the (...) monitors, the syringe pumps, the actions of the surgeon or even from alterations in patients. This could produce adverse side effects that can affect the patient postoperative and reduce the safety of the patient in the operating room. Then, the use of anomaly detection techniques plays a significant role to avoid this undesirable situations. This work assesses different one-class intelligent techniques to detect anomalies in patients undergoing general anesthesia. Due to the difficulty of obtaining real data from anomaly situations, artificial outliers are generated to check the performance of each classifier. The final model presents successful performance. (shrink)

As it is well known, mobile phones have become a basic gadget for any individual that usually stores sensitive information. This mainly motivates the increase in the number of attacks aimed at jeopardizing smartphones, being an extreme concern above all on Android OS, which is the most popular platform in the market. Consequently, a strong effort has been devoted for mitigating mentioned incidents in recent years, even though few researchers have addressed the application of visualization techniques for the analysis of (...) malware. Within this field, the present work proposes the extension of a new technique called Hybrid Unsupervised Exploratory Plots to visualize Android malware datasets. More precisely, the novel Beta-Hebbian Learning (BHL) method is applied for the first time and validated under the frame of Hybrid Unsupervised Exploratory Plots, in conjunction with clustering methods. The informative visualization achieved provides a picture of the structure of the malware families, allowing subsequent analysis of their organization. To validate the Hybrid Unsupervised Exploratory Plot extension and its tuning, the popular Android Malware Genome dataset has been used in the experimental setting. Promising results have been obtained, suggesting that BHL applied in combination with clustering techniques in Hybrid Unsupervised Exploratory Plots are a viable resource for the visualization of malware families. (shrink)

The present research describes a novel adaptive anomaly detection method to optimize the performance of nonlinear and time-varying systems. The proposal integrates a centroid-based approach with the real-time identification technique Recursive Least Squares. In order to find anomalies, the approach compares the present system dynamics with the average (centroid) of the dynamics found in earlier states for a given setpoint. The system labels the dynamics difference as an anomaly if it rises over a determinate threshold. To validate the proposal, two (...) different datasets obtained from a level control plant operation have been used, to which anomalies have been artificially added. The results shown have determined a satisfactory performance of the method, especially in those processes with low noise. (shrink)

Automatic control of physiological variables is one of the most active areas in biomedical engineering. This paper is centered in the prediction of the analgesic variables evolution in patients undergoing surgery. The proposal is based on the use of hybrid intelligent modelling methods. The study considers the Analgesia Nociception Index to assess the pain in the patient and remifentanil as intravenous analgesic. The model proposed is able to make a one-step-ahead prediction of the remifentanil dose corresponding to the current state (...) of the patient. The input information is the previous remifentanil dose, the ANI variable and the electromyogram signal. Modelling techniques used are Artificial Neural Networks and Support Vector machines for Regression combined with clustering methods. Both training and validation were done with a real dataset from different patients. Results obtained show the potential of this methodology to calculate the drug dose corresponding to a given analgesic state of the patient. (shrink)

Tuberculosis en América Latina y el Caribe: reflexiones desde la bioética Tuberculose na América Latina e no Caribe: reflexões da bioética The objective of this article is to analyze the conditions of access to health services by people with tuberculosis in Latin America and the Caribbean, reflecting on the public health aspects involved from a bioethical perspective. A literature review of the context of tuberculosis in LAC based on epidemiological data was performed. The results were analyzed from its relationship with (...) the social determinants of health and the ethical principles that guide medical practice. Tuberculosis is a pressing public health problem in the region because of its family, social, economic and health impact. It mainly affects vulnerable individuals and populations. Health services violate ethical principles. Tuberculosis is a serious ethics and public health problem in the region that causes death, disability and increased poverty. It is imperative to ensure the right to health services and to understand the individual and public health consequences of non-adherence to treatment. It is important that national tuberculosis control strategies include principles of dignity and non-discrimination of the sick, changes in the social determinants of the disease, and respect for the ethnicity, language culture and identity of patients. Para citar este artículo / To reference this article / Para citar este artigo Muñoz del Carpio-Toia A, Sánchez-Pérez HJ, Verges de López C, López-Dávila LM, Sotomayor-Saavedra MA, Sorokin P. Tuberculosis en América Latina y el Caribe: reflexiones desde la bioética. pers. bioét. 2018; 22: 331-357. DOI: 10.5294/pebi.2018.22.2.10. (shrink)

RESUMEN La problemática del muy bajo peso al nacer ha sido abordada desde hace varios años, sin embargo, las investigaciones están enfocadas desde diferentes perspectivas y contextos, no siempre se ha considerado su repercusión a corto y a largo plazo, así como la interacción de los diferentes factores que se relacionan con este riesgo biológico. Por ello en esta revisión bibliográfica se realiza una valoración de estudios ejecutados a nivel internacional y en Cuba dedicados al desarrollo neuropsicológico de niños con (...) muy bajo peso al nacer. Se concluye que el muy bajo peso al nacer repercute en el desarrollo neuropsicológicos desde edades tempranas, hasta la adolescencia; por ello es necesario una visión integradora que tenga en cuenta el riesgo biológico, las particularidades individuales y el contexto social en que se desenvuelve el niño desde los primeros momentos, lo que posibilitará, perfeccionar la atención a corto y largo plazo al grupo de riesgo. ABSTRACT The problems of very low birth weight have been dealt with for many years, however, research on the matter is approached from different perspectives and contexts, not always have its short and long term repercussions being considered as well as the interaction of different factors related to this biological risk. Therefore, this bibliographical review makes an assessment of international and Cuban studies devoted to very low birth weight children’s neuropsychological development. It was reached the conclusion that very low birth weight affects neuropsychological development from early ages to adolescence; for that reason, it is necessary to have an integrated approach of the problem that takes into account the biologicals risk, individual characteristics and the social context in which the child develops from the beginning, which will make the improvement of short and long term care to this risk group possible. (shrink)

Ao evidenciar que as relações estabelecidas por homens e mulheres com o meio concreto engendram o real, a dialética torna exequível a revolução do status quo por possibilitar a compreensão de que o mundo é sempre resultado da práxis humana, seja ela marcada por relações de dominação que reificam e fetichizam a prática social, seja marcada por relações que operam a humanização dos homens e mulheres. Ao romper com os fetiches, ou seja, ao perceber que os objetos não devem sujeitá-los, (...) homens e mulheres avançam de encontro à reificação, alçando-se a possibilidade de revolucionar suas condições de existência. Assim, o rompimento da pseudoconcreticidade ocorre no momento em que se evidencia que a realidade social se concretiza por meio das condições de produção e reprodução da existência social das pessoas, que é em nossa sociedade marcada pela luta de classes. Este processo de rompimento exige um esforço construtor de uma interpretação do real que vá para além de uma representação caótica do todo, típico das vivências cotidianas. Este artigo postula que o método materialista histórico dialético pode auxiliar neste processo. Partindo desta constatação, elabora-se reflexão sobre este método de análise do real. By showing that the relationships established by men and women with the practical means to engender real, dialectic makes possible the revolution of the status quo by allowing the understanding that the world is always the result of human practice, it is marked by relations of domination that fetishize and reify the social practice or marked by relationships that operate at the humanization of men and women. By breaking with the fetishes, or to realize that objects should not expose them, men and women advance against reification, raising the possibility of revolutionizing his conditions of existence. Thus, disruption of pseudoconcreticity occurs at the moment is evident that social reality is concretized through the conditions of production and reproduction of social existence, which is in our society marked by class struggle. This process requires a breakout effort to construct an interpretation of reality that go beyond a representation of the whole chaotic, typical of everyday experiences. This article posits that the historical materialist dialectical method con help this process. Based on this observation, we undertake reflection on this method of analysis of the real. (shrink)

For millennia, knowledge has eluded a precise definition. The industrialization of knowledge (IoK) and the associated proliferation of the so-called knowledge communities in the last few decades caused this state of affairs to deteriorate, namely by creating a trio composed of data, knowledge, and information (DIK) that is not unlike the aporia of the trinity in philosophy. This calls for a general theory of knowledge (ToK) that can work as a foundation for a science of knowledge (SoK) and additionally distinguishes (...) knowledge from both data and information. In this paper, I attempt to sketch this generality via the establishing of both knowledge structures and knowledge systems that can then be adopted/adapted by the diverse communities for the respective knowledge technologies and practices. This is achieved by means of a formal–indeed, mathematical–approach to epistemological matters a.k.a. formal epistemology. The corresponding application focus is on knowledge systems implementable as computer programs. (shrink)

Cosmopolitanism is said by many critics to be arrogant. In emphasizing universal principles and granting no fundamental moral significance to national or other group belonging, it wrongly treats those making non-universalist claims as not authorized to speak, while treating those in non-Western societies as not qualified. This book works to address such objections. It does so in part by engaging the work of B.R. Ambedkar, architect of India's 1950 Constitution and revered champion of the country's Dalits (formerly "untouchables"). Ambedkar cited (...) universal principles of equality and rights in confronting domestic exclusions and the "arrogance" of caste. He sought to advance forms of political humility, or the affirmation of equal standing within political institutions and openness to input and challenge within them. This book examines how an "institutional global citizenship" approach to cosmopolitanism could similarly advance political humility, in supporting the development of input and challenge mechanisms beyond the state. It employs a grounded normative theory method, taking insights for the model from field research among Dalit activists pressing for domestic reforms through the UN human rights regime, and from their critics in the Hindu nationalist Bharatiya Janata Party. Insights also are taken from Turkish protesters challenging a rising domestic authoritarianism, and from UK Independence Party members demanding "Brexit" from the European Union-in part because of possibilities that predominantly Muslim Turkey will join. Overall, it is shown, an appropriately configured institutional cosmopolitanism should orient fundamentally to political humility rather than arrogance, while holding significant potential for advancing global rights protections and more equitable rights specifications. (shrink)

El 23 de abril de 1996 falleció en Lima, a los 89 años, el padre Gerardo Alarco Larrabure, profesor de filosofía medieval de la mayoría de los miembros del comité editorial de Areté. Estos apuntes biográficos, que se limitan a su formación intelectual hasta su retorno de Europa al Perú en 1945, pretenden ser un homenaje a su persona y una muestra de gratitud por su labor docente.

The essays in this volume investigate the norms of reason--the standards which contribute to determining whether beliefs, inferences, and actions are rational. Nine philosophers and two psychologists discuss what kinds of things these norms are, how they can be situated within the natural world, and what role they play in the psychological explanation of belief and action. Current work in the theory of rationality is subject to very diverse influences ranging from experimental and theoretical psychology, through philosophy of logic and (...) language, to metaethics and the theory of practical reasoning; this range is well represented here. (shrink)