The typic in Kant’s critique of practical reason : moral judgment and symbolic representation

Comment pouvons-nous représenter un principe moral universel de manière à le rendre applicable à des cas concrets ? Ce problème revêt une forme aiguë dans la philosophie morale d’Emmanuel Kant (1724-1804), tout particulièrement dans sa théorie du jugement moral, car il soutient que l’on doit appliquer la loi morale « suprasensible » à des actions dans le monde sensible afin de déterminer celles-ci comme moralement bonnes ou mauvaises. Kant aborde ce problème dans un chapitre de la Critique de la raison pratique (1788) intitulé « De la typique de la faculté de juger pratique pure » (KpV 5: 67-71). La première partie de la thèse vise à fournir un commentaire compréhensif et détaillé de ce texte important, mais trop peu étudié. Étant donné que la loi morale, en tant qu’Idée suprasensible de la raison, ne peut pas être appliquée directement à des actions dans l’intuition sensible, Kant a recours à une forme particulière de représentation indirecte et symbolique. Sa solution inédite consiste à fournir la faculté de juger avec un « type [Typus] », ou analogue formel, de la loi morale. Ce type est la loi de la causalité naturelle : en tant que loi, il sert d’étalon formel pour tester l’universalisabilité des maximes ; et, en tant que loi de la nature, il peut aussi s’appliquer à toute action dans l’expérience sensible. Dès lors, le jugement moral s’effectue par le biais d’une expérience de pensée dans laquelle on se demande si l’on peut vouloir que sa maxime devienne une loi universelle d’une nature contrefactuelle dont on ferait soi-même partie. Cette expérience de pensée fonctionne comme une « épreuve [Probe] » de la forme des maximes et, par ce moyen, du statut moral des actions. Kant soutient que tout un chacun, même « l’entendement le plus commun », emploie cette procédure pour l’appréciation morale. De plus, la typique prémunit contre deux menaces à l’éthique rationaliste de Kant, à savoir l’empirisme (c’est-à-dire le conséquentialisme) et le mysticisme. La seconde partie de la thèse se penche sur l’indication de Kant que la typique « ne sert que comme un symbole ». Un bon nombre de commentateurs ont voulu assimiler la typique à la notion d’« hypotypose symbolique » présentée dans le § 59 de la Critique de la faculté de juger (1790). La typique serait un processus de symbolisation esthétique consistant à présenter, de façon indirecte, la représentation abstraite de la loi morale sous la forme d’un symbole concret et intuitif. Dans un premier chapitre, cette interprétation est présentée et soumise à un examen critique qui cherche à montrer qu’elle est erronée et peu judicieuse. Dans le second chapitre, nous poursuivons une voie d’interprétation jusqu’ici ignorée, montrant que la typique a de plus grandes continuités avec la notion d’« anthropomorphisme symbolique », une procédure strictement analogique introduite auparavant dans les Prolégomènes (1783). Nous en concluons, d’une part, que la typique fut un moment décisif dans l’évolution de la théorie kantienne de la représentation symbolique et que, d’autre part, elle marque la réalisation, chez Kant, d’une conception proprement critique de la nature et de la morale comme deux sphères distinctes, dont la médiation s’opère par le biais des concepts de loi et de conformité à la loi (Gesetzmässigkeit). En un mot, la typique s’avère l’instrument par excellence du « rationalisme de la faculté de juger ».

RECHERCHE TRANSLATIONNELLE EN NEUROSCIENCES PSYCHIATRIQUES: DE L'ANIMAL MODELE DE SCHIZOPHRENIE A LA DETECTION D'UNE DESORIENTATION SPATIALE, PRATIQUE OU SYMBOLIQUE CHEZ DES PATIENTS

La modélisation, chez l'animal, de maladies psychiatriques telles que la schizophrénie repose sur différentes démarches visant à induire des perturbations cérébrales similaires à celles observées dans la maladie. Nous avons cherché à étudier chez le rat les effets d'une diminution (50%) transitoire en glutathion (GSH) durant le développement (PND 5 à PND 16) à partir de l'implication, chez des adultes, des conséquences de cette perturbation dans des mécanismes fondamentaux de traitement de l'information sensorielle. Cette thèse évalue et documente les déficits de compétences de navigation spatiale dans ce modèle. Nous avons mis en évidence des effets comportementaux à partir de l'identification de différences particulières dans des tâches d'orientation: des difficultés, chez les rats ayant subi un déficit en GSH, à élaborer une représentation globale de l'environnement dans lequel ils se déplacent, difficultés compensées par une attention particulière aux détails visuels le composant. Cette stratégie réactive compensatoire est efficace lorsque les conditions permettent un ajustement continu aux repères visuels environnementaux. Elle ne permet cependant pas des prédictions et des attentes sur ce qui devrait être rencontré et perçu dans une certaine direction, dès qu'une partie des informations visuelles familières disparaît. Il faudrait pour cela une capacité fondée sur une représentation abstraite, à distance des modalités sensorielles qui en ont permis son élaboration. Notre thèse soutient que les déficits, supposés participer à l'émergence de certains symptômes de la maladie, auraient également des conséquences sur l'élaboration de la représentation spatiale nécessaire à des capacités d'orientation effectives et symboliques. - The study of a psychiatric disease such as schizophrenia in an animal model relies on different approaches attempting to replicate brain perturbations similar to those observed in the illness. In the present work, behavioural consequences of a functional deficit in brain connectivity and coordination were assessed in rats with a transitory glutathione (GSH) deficit induced during the postnatal development (PND 5-PND 16) with daily injections of BSO (1- buthionine-(S,R)- sulfoximine). We searched for a theoretical syndrome associating ecologically relevant behavioural adaptive deficits and resulting from the weakening of sensory integration processes. Our results revealed significant and specific deficit of BSO treated rats in spatial orientation tasks designed to test for cognitive mapping abilities. Treated rats behaved as if impaired in the proactive strategies supported by an abstract representation such as a cognitive map. In contrast their performances were preserved whenever the environmental conditions allowed for adaptative reactive strategies, an equivalent of the visual affordances described by Gibson (1958). This supports our thesis that BSO treated rats expressed difficulties in elaborating a global representation of the environment. This deficit was completely - or - partially compensated by the development of an increased attention to the environment's visual details. This compensatory reactive strategy requires a rich environment allowing for continuous adjustment to visual cues. However, such adjustment doesn't allow to predictions and expectancies about what should be met and perceived in a certain direction, when familiar visual spatial cues are missing. Such competencies require orientation based on the use of an abstract spatial representation, independent from the specific sensory modalities that have participated to its elaboration. The impairment of BSO rats such spatial representation could result from a deficit in the integration and organization of perceptual information. Our model leads to the hypothesis that these fundamental deficits might account for certain symptoms of schizophrenia. They would also interfere with in the capacity to elaborate spatial representation necessary for optimal orientation in natural, artificial or symbolic environment.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Modèle informatique du coapprentissage des ganglions de la base et du cortex : l'apprentissage par renforcement et le développement de représentations

Tout au long de la vie, le cerveau développe des représentations de son environnement permettant à l’individu d’en tirer meilleur profit. Comment ces représentations se développent-elles pendant la quête de récompenses demeure un mystère. Il est raisonnable de penser que le cortex est le siège de ces représentations et que les ganglions de la base jouent un rôle important dans la maximisation des récompenses. En particulier, les neurones dopaminergiques semblent coder un signal d’erreur de prédiction de récompense. Cette thèse étudie le problème en construisant, à l’aide de l’apprentissage machine, un modèle informatique intégrant de nombreuses évidences neurologiques. Après une introduction au cadre mathématique et à quelques algorithmes de l’apprentissage machine, un survol de l’apprentissage en psychologie et en neuroscience et une revue des modèles de l’apprentissage dans les ganglions de la base, la thèse comporte trois articles. Le premier montre qu’il est possible d’apprendre à maximiser ses récompenses tout en développant de meilleures représentations des entrées. Le second article porte sur l'important problème toujours non résolu de la représentation du temps. Il démontre qu’une représentation du temps peut être acquise automatiquement dans un réseau de neurones artificiels faisant office de mémoire de travail. La représentation développée par le modèle ressemble beaucoup à l’activité de neurones corticaux dans des tâches similaires. De plus, le modèle montre que l’utilisation du signal d’erreur de récompense peut accélérer la construction de ces représentations temporelles. Finalement, il montre qu’une telle représentation acquise automatiquement dans le cortex peut fournir l’information nécessaire aux ganglions de la base pour expliquer le signal dopaminergique. Enfin, le troisième article évalue le pouvoir explicatif et prédictif du modèle sur différentes situations comme la présence ou l’absence d’un stimulus (conditionnement classique ou de trace) pendant l’attente de la récompense. En plus de faire des prédictions très intéressantes en lien avec la littérature sur les intervalles de temps, l’article révèle certaines lacunes du modèle qui devront être améliorées. Bref, cette thèse étend les modèles actuels de l’apprentissage des ganglions de la base et du système dopaminergique au développement concurrent de représentations temporelles dans le cortex et aux interactions de ces deux structures.

A novel shape feature for fast region-based pedestrian recognition

A new class of shape features for region classification and high-level recognition is introduced. The novel Randomised Region Ray (RRR) features can be used to train binary decision trees for object category classification using an abstract representation of the scene. In particular we address the problem of human detection using an over segmented input image. We therefore do not rely on pixel values for training, instead we design and train specialised classifiers on the sparse set of semantic regions which compose the image. Thanks to the abstract nature of the input, the trained classifier has the potential to be fast and applicable to extreme imagery conditions. We demonstrate and evaluate its performance in people detection using a pedestrian dataset.

Schopenhauer e os conhecimentos intuitivo e abstrato

Pós-graduação em Filosofia - FFC

Algoritmos de distribución de cargas de proceso en computación con membranas

Con el surgir de los problemas irresolubles de forma eficiente en tiempo polinomial en base al dato de entrada, surge la Computación Natural como alternativa a la computación clásica. En esta disciplina se trata de o bien utilizar la naturaleza como base de cómputo o bien, simular su comportamiento para obtener mejores soluciones a los problemas que los encontrados por la computación clásica. Dentro de la computación natural, y como una representación a nivel celular, surge la Computación con Membranas. La primera abstracción de las membranas que se encuentran en las células, da como resultado los P sistemas de transición. Estos sistemas, que podrían ser implementados en medios biológicos o electrónicos, son la base de estudio de esta Tesis. En primer lugar, se estudian las implementaciones que se han realizado, con el fin de centrarse en las implementaciones distribuidas, que son las que pueden aprovechar las características intrínsecas de paralelismo y no determinismo. Tras un correcto estudio del estado actual de las distintas etapas que engloban a la evolución del sistema, se concluye con que las distribuciones que buscan un equilibrio entre las dos etapas (aplicación y comunicación), son las que mejores resultados presentan. Para definir estas distribuciones, es necesario definir completamente el sistema, y cada una de las partes que influyen en su transición. Además de los trabajos de otros investigadores, y junto a ellos, se realizan variaciones a los proxies y arquitecturas de distribución, para tener completamente definidos el comportamiento dinámico de los P sistemas. A partir del conocimiento estático –configuración inicial– del P sistema, se pueden realizar distribuciones de membranas en los procesadores de un clúster para obtener buenos tiempos de evolución, con el fin de que la computación del P sistema sea realizada en el menor tiempo posible. Para realizar estas distribuciones, hay que tener presente las arquitecturas –o forma de conexión– de los procesadores del clúster. La existencia de 4 arquitecturas, hace que el proceso de distribución sea dependiente de la arquitectura a utilizar, y por tanto, aunque con significativas semejanzas, los algoritmos de distribución deben ser realizados también 4 veces. Aunque los propulsores de las arquitecturas han estudiado el tiempo óptimo de cada arquitectura, la inexistencia de distribuciones para estas arquitecturas ha llevado a que en esta Tesis se probaran las 4, hasta que sea posible determinar que en la práctica, ocurre lo mismo que en los estudios teóricos. Para realizar la distribución, no existe ningún algoritmo determinista que consiga una distribución que satisfaga las necesidades de la arquitectura para cualquier P sistema. Por ello, debido a la complejidad de dicho problema, se propone el uso de metaheurísticas de Computación Natural. En primer lugar, se propone utilizar Algoritmos Genéticos, ya que es posible realizar alguna distribución, y basada en la premisa de que con la evolución, los individuos mejoran, con la evolución de dichos algoritmos, las distribuciones también mejorarán obteniéndose tiempos cercanos al óptimo teórico. Para las arquitecturas que preservan la topología arbórea del P sistema, han sido necesarias realizar nuevas representaciones, y nuevos algoritmos de cruzamiento y mutación. A partir de un estudio más detallado de las membranas y las comunicaciones entre procesadores, se ha comprobado que los tiempos totales que se han utilizado para la distribución pueden ser mejorados e individualizados para cada membrana. Así, se han probado los mismos algoritmos, obteniendo otras distribuciones que mejoran los tiempos. De igual forma, se han planteado el uso de Optimización por Enjambres de Partículas y Evolución Gramatical con reescritura de gramáticas (variante de Evolución Gramatical que se presenta en esta Tesis), para resolver el mismo cometido, obteniendo otro tipo de distribuciones, y pudiendo realizar una comparativa de las arquitecturas. Por último, el uso de estimadores para el tiempo de aplicación y comunicación, y las variaciones en la topología de árbol de membranas que pueden producirse de forma no determinista con la evolución del P sistema, hace que se deba de monitorizar el mismo, y en caso necesario, realizar redistribuciones de membranas en procesadores, para seguir obteniendo tiempos de evolución razonables. Se explica, cómo, cuándo y dónde se deben realizar estas modificaciones y redistribuciones; y cómo es posible realizar este recálculo. Abstract Natural Computing is becoming a useful alternative to classical computational models since it its able to solve, in an efficient way, hard problems in polynomial time. This discipline is based on biological behaviour of living organisms, using nature as a basis of computation or simulating nature behaviour to obtain better solutions to problems solved by the classical computational models. Membrane Computing is a sub discipline of Natural Computing in which only the cellular representation and behaviour of nature is taken into account. Transition P Systems are the first abstract representation of membranes belonging to cells. These systems, which can be implemented in biological organisms or in electronic devices, are the main topic studied in this thesis. Implementations developed in this field so far have been studied, just to focus on distributed implementations. Such distributions are really important since they can exploit the intrinsic parallelism and non-determinism behaviour of living cells, only membranes in this case study. After a detailed survey of the current state of the art of membranes evolution and proposed algorithms, this work concludes that best results are obtained using an equal assignment of communication and rules application inside the Transition P System architecture. In order to define such optimal distribution, it is necessary to fully define the system, and each one of the elements that influence in its transition. Some changes have been made in the work of other authors: load distribution architectures, proxies definition, etc., in order to completely define the dynamic behaviour of the Transition P System. Starting from the static representation –initial configuration– of the Transition P System, distributions of membranes in several physical processors of a cluster is algorithmically done in order to get a better performance of evolution so that the computational complexity of the Transition P System is done in less time as possible. To build these distributions, the cluster architecture –or connection links– must be considered. The existence of 4 architectures, makes that the process of distribution depends on the chosen architecture, and therefore, although with significant similarities, the distribution algorithms must be implemented 4 times. Authors who proposed such architectures have studied the optimal time of each one. The non existence of membrane distributions for these architectures has led us to implement a dynamic distribution for the 4. Simulations performed in this work fix with the theoretical studies. There is not any deterministic algorithm that gets a distribution that meets the needs of the architecture for any Transition P System. Therefore, due to the complexity of the problem, the use of meta-heuristics of Natural Computing is proposed. First, Genetic Algorithm heuristic is proposed since it is possible to make a distribution based on the premise that along with evolution the individuals improve, and with the improvement of these individuals, also distributions enhance, obtaining complexity times close to theoretical optimum time. For architectures that preserve the tree topology of the Transition P System, it has been necessary to make new representations of individuals and new algorithms of crossover and mutation operations. From a more detailed study of the membranes and the communications among processors, it has been proof that the total time used for the distribution can be improved and individualized for each membrane. Thus, the same algorithms have been tested, obtaining other distributions that improve the complexity time. In the same way, using Particle Swarm Optimization and Grammatical Evolution by rewriting grammars (Grammatical Evolution variant presented in this thesis), to solve the same distribution task. New types of distributions have been obtained, and a comparison of such genetic and particle architectures has been done. Finally, the use of estimators for the time of rules application and communication, and variations in tree topology of membranes that can occur in a non-deterministic way with evolution of the Transition P System, has been done to monitor the system, and if necessary, perform a membrane redistribution on processors to obtain reasonable evolution time. How, when and where to make these changes and redistributions, and how it can perform this recalculation, is explained.

Interfacing ASM with the MDG tool

In this paper we describe an approach to interface Abstract State Machines (ASM) with Multiway Decision Graphs (MDG) to enable tool support for the formal verification of ASM descriptions. ASM is a specification method for software and hardware providing a powerful means of modeling various kinds of systems. MDGs are decision diagrams based on abstract representation of data and axe used primarily for modeling hardware systems. The notions of ASM and MDG axe hence closely related to each other, making it appealing to link these two concepts. The proposed interface between ASM and MDG uses two steps: first, the ASM model is transformed into a flat, simple transition system as an intermediate model. Second, this intermediate model is transformed into the syntax of the input language of the MDG tool, MDG-HDL. We have successfully applied this transformation scheme on a case study, the Island Tunnel Controller, where we automatically generated the corresponding MDG-HDL models from ASM specifications.

TRANSFORMATIONS OF TASK-DEPENDENT PLASTICITY FROM A1 TO HIGHER-ORDER AUDITORY CORTEX

Everyday, humans and animals navigate complex acoustic environments, where multiple sound sources overlap. Somehow, they effortlessly perform an acoustic scene analysis and extract relevant signals from background noise. Constant updating of the behavioral relevance of ambient sounds requires the representation and integration of incoming acoustical information with internal representations such as behavioral goals, expectations and memories of previous sound-meaning associations. Rapid plasticity of auditory representations may contribute to our ability to attend and focus on relevant sounds. In order to better understand how auditory representations are transformed in the brain to incorporate behavioral contextual information, we explored task-dependent plasticity in neural responses recorded at four levels of the auditory cortical processing hierarchy of ferrets: the primary auditory cortex (A1), two higher-order auditory areas (dorsal PEG and ventral-anterior PEG) and dorso-lateral frontal cortex. In one study we explored the laminar profile of rapid-task related plasticity in A1 and found that plasticity occurred at all depths, but was greatest in supragranular layers. This result suggests that rapid task-related plasticity in A1 derives primarily from intracortical modulation of neural selectivity. In two other studies we explored task-dependent plasticity in two higher-order areas of the ferret auditory cortex that may correspond to belt (secondary) and parabelt (tertiary) auditory areas. We found that representations of behaviorally-relevant sounds are progressively enhanced during performance of auditory tasks. These selective enhancement effects became progressively larger as you ascend the auditory cortical hierarchy. We also observed neuronal responses to non-auditory, task-related information (reward timing, expectations) in the parabelt area that were very similar to responses previously described in frontal cortex. These results suggests that auditory representations in the brain are transformed from the more veridical spectrotemporal information encoded in earlier auditory stages to a more abstract representation encoding sound behavioral meaning in higher-order auditory areas and dorso-lateral frontal cortex.

The Reform Bill: 2 William IV. Cap. 45 : Abstract of an act to amend the representation of the people, in England and Wales, passed 7th January, 1832.

Mode of access: Internet.

Cartographic representation of spatiotemporal phenomena

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Social representation of Alzheimer's disease for family caregivers: stressful and rewarding

Abstract OBJECTIVE To understand the content of Social Representation (SR) of family caregivers of Alzheimer's disease patients. METHOD Interviews were conducted with 26 caregivers and analyzed by the ALCESTE software. RESULTS The SR content was structured in two thematic axes called Daily Life and Care and Medical and Emotional Concepts and Outcomes. The first axis creates images related to the routine of interaction with the sick person, and contains a description of care procedures, experiences, and practices applied every day. The second is composed of subjective and conceptual aspects that make up the social representation of Alzheimer's disease, with meanings related to the emotional, medical, and biological contexts. CONCLUSION Due to the importance of topics related to patients' dependence and the personal and emotional consequences of the disease, overload is the main content of the SR of Alzheimer's disease for caregivers, and the understanding of these SR by health professionals should support the planning of interventions addressing this group of individuals.

The Sanskrit epics' representation of Vedic myths

Abstract: This book studies several mythical motifs, found in the Veda (especially in the Ùgveda) on the one hand and in one or both Sanskrit epics on the other: Agni's hiding, the theft of the Soma, Indra's rape of Ahalyå, Upamanyu's salvation by the Aßvins, and finally the representation of the Great War of the Mahåbhårata as a sacrifice. While it is often said that the subsequent Indian literature only paid "lipservice" to the Vedas without really knowing and even less understanding these texts, the present study not only shows that many Vedic myths are still kept alive in the Epics, but more importantly that their deep underlying meaning was perfectly understood by the epic mythmakers, and reactualized to fit the changed religious conditions of epic times. Résumé: Descriptif du livre Ce livre étudie plusieur motifs mythologiques qui se trouvent à la fois dans les Vedas (et spécialement dans le Ùgveda), et dans l'une ou l'autre des grandes épopées sanskrites, le Mahåbhårata et le Råmåyana. Ces motifs sont: la disparition d'Agni, le rapt du Soma, le viol d'Ahalyå par Indra, le sauvetage d'Upamanyu par les Aßvins, et enfin, la représentation de la grande guerre du Mahåbhårata comme un rite sacrificiel. On maintient souvent que la littérature plus tardive ne fait référence aux Vedas que pour la forme, sans pour autant réellement connaître et encore moins comprendre ces textes. Mais la présente étude montre tout au contraire que non seulement beaucoup de mythes védiques se retrouvent dans les épopées, mais encore ? ce qui est plus important ? que les mythographes de l'épopée avaient parfaitement compris leur sens profond, et l'avaient réactualisé pour répondre aux changements religieux de l'époque épique.