Academic literature on the topic 'Raisonnement computationnel'
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Journal articles on the topic "Raisonnement computationnel"
Gardin, Jean-Claude. "Archéologie, formalisation et sciences sociales." Sociologie et sociétés 31, no. 1 (October 2, 2002): 119–27. http://dx.doi.org/10.7202/001282ar.
Full textDissertations / Theses on the topic "Raisonnement computationnel"
Ballout, Ali. "Apprentissage actif pour la découverte d'axiomes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4026.
Full textThis thesis addresses the challenge of evaluating candidate logical formulas, with a specific focus on axioms, by synergistically combining machine learning with symbolic reasoning. This innovative approach facilitates the automatic discovery of axioms, primarily in the evaluation phase of generated candidate axioms. The research aims to solve the issue of efficiently and accurately validating these candidates in the broader context of knowledge acquisition on the semantic Web.Recognizing the importance of existing generation heuristics for candidate axioms, this research focuses on advancing the evaluation phase of these candidates. Our approach involves utilizing these heuristic-based candidates and then evaluating their compatibility and consistency with existing knowledge bases. The evaluation process, which is typically computationally intensive, is revolutionized by developing a predictive model that effectively assesses the suitability of these axioms as a surrogate for traditional reasoning. This innovative model significantly reduces computational demands, employing reasoning as an occasional "oracle" to classify complex axioms where necessary.Active learning plays a pivotal role in this framework. It allows the machine learning algorithm to select specific data for learning, thereby improving its efficiency and accuracy with minimal labeled data. The thesis demonstrates this approach in the context of the semantic Web, where the reasoner acts as the "oracle," and the potential new axioms represent unlabeled data.This research contributes significantly to the fields of automated reasoning, natural language processing, and beyond, opening up new possibilities in areas like bioinformatics and automated theorem proving. By effectively marrying machine learning with symbolic reasoning, this work paves the way for more sophisticated and autonomous knowledge discovery processes, heralding a paradigm shift in how we approach and leverage the vast expanse of data on the semantic Web
Romdhane, Lofti Ben. "Computational networks & competition-based models : solving complex causal interactions." Sherbrooke : Université de Sherbrooke, 2000.
Find full textKramdi, Seifeddine. "A modal approach to model computational trust." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30146/document.
Full textThe concept of trust is a socio-cognitive concept that plays an important role in representing interactions within concurrent systems. When the complexity of a computational system and its unpredictability makes standard security solutions (commonly called hard security solutions) inapplicable, computational trust is one of the most useful concepts to design protocols of interaction. In this work, our main objective is to present a prospective survey of the field of study of computational trust. We will also present two trust models, based on logical formalisms, and show how they can be studied and used. While trying to stay general in our study, we use service-oriented architecture paradigm as a context of study when examples are needed. Our work is subdivided into three chapters. The first chapter presents a general view of the computational trust studies. Our approach is to present trust studies in three main steps. Introducing trust theories as first attempts to grasp notions linked to the concept of trust, fields of application, that explicit the uses that are traditionally associated to computational trust, and finally trust models, as an instantiation of a trust theory, w.r.t. some formal framework. Our survey ends with a set of issues that we deem important to deal with in priority in order to help the advancement of the field. The next two chapters present two models of trust. Our first model is an instantiation of Castelfranchi & Falcone's socio-cognitive trust theory. Our model is implemented using a Dynamic Epistemic Logic that we propose. The main originality of our solution is the fact that our trust definition extends the original model to complex action (programs, composed services, etc.) and the use of authored assignment as a special kind of atomic actions. The use of our model is then illustrated in a case study related to service-oriented architecture. Our second model extends our socio-cognitive definition to an abductive framework that allows us to associate trust to explanations. Our framework is an adaptation of Bochman's production relations to the epistemic case. Since Bochman approach was initially proposed to study causality, our definition of trust in this second model presents trust as a special case of causal reasoning, applied to a social context. We end our manuscript with a conclusion that presents how we would like to extend our work
Charrier, Tristan. "Complexité théorique du raisonnement en logique épistémique dynamique et étude d’une approche symbolique." Thesis, Rennes 1, 2018. https://ged.univ-rennes1.fr/nuxeo/site/esupversions/2a4b2a55-42ff-4768-9b9e-677421fef507.
Full textWe study the theoretical complexity of reasoning tasks involving knowledge in multi-agent systems. We consider dynamic epistemic logic (DEL) as a natural way of expressing knowledge, which allows to express nested knowledge of agents and partially observed dynamic actions. We show complexity results for model checking and satisfiability of DEL formulas, and define a symbolic approach for these problems. We also study DEL-based planning and quantification over specific actions: public announcements
Berreby, Fiona. "Models of Ethical Reasoning." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS137.
Full textThis thesis is part of the ANR eThicAa project, which has aimed to define moral autonomous agents, provide a formal representation of ethical conflicts and of their objects (within one artificial moral agent, between an artificial moral agent and the rules of the system it belongs to, between an artificial moral agent and a human operator, between several artificial moral agents), and design explanation algorithms for the human user. The particular focus of the thesis pertains to exploring ethical conflicts within a single agent, as well as designing explanation algorithms. The work presented here investigates the use of high-level action languages for designing such ethically constrained autonomous agents. It proposes a novel and modular logic-based framework for representing and reasoning over a variety of ethical theories, based on a modified version of the event calculus and implemented in Answer Set Programming. The ethical decision-making process is conceived of as a multi-step procedure captured by four types of interdependent models which allow the agent to represent situations, reason over accountability and make ethically informed choices. More precisely, an action model enables the agent to appraise its environment and the changes that take place in it, a causal model tracks agent responsibility, a model of the Good makes a claim about the intrinsic value of goals or events, and a model of the Right considers what an agent should do, or is most justified in doing, given the circumstances of its actions. The causalmodel plays a central role here, because it permits identifying some properties that causal relations assume and that determine how, as well as to what extent, we may ascribe ethical responsibility on their basis. The overarching ambition of the presented research is twofold. First, to allow the systematic representation of an unbounded number of ethical reasoning processes, through a framework that is adaptable and extensible by virtue of its designed hierarchisation and standard syntax. Second, to avoid the pitfall of some works in current computational ethics that too readily embed moralinformation within computational engines, thereby feeding agents with atomic answers that fail to truly represent underlying dynamics. We aim instead to comprehensively displace the burden of moral reasoning from the programmer to the program itself
Mercier, Chloé. "Modéliser les processus cognitifs dans une tâche de résolution créative de problème : des approches symboliques à neuro-symboliques en sciences computationnelles de l'éducation." Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0065.
Full textIntegrating transversal skills such as creativity, problem solving and computational thinking, into the primary and secondary curricula is a key challenge in today’s educational field. We postulate that teaching and assessing transversal competencies could benefit from a better understanding of the learners’ behaviors in specific activities that require these competencies. To this end, computational learning science is an emerging field that requires the close collaboration of computational neuroscience and educational sciences to enable the assessment of learning processes. We focus on a creative problem-solving task in which the subject is engaged into building a “vehicle” by combining modular robotic cubes. As part of an exploratory research action, we propose several approaches based on symbolic to neuro-symbolic formalisms, in order to specify such a task and model the behavior and underlying cognitive processes of a subject engaged in this task. Despite being at a very preliminary stage, such a formalization seems promising to better understand complex mechanisms involved in creative problem solving at several levels: (i) the specification of the problem and the observables of interest to collect during the task; (ii) the cognitive representation of the problem space, depending on prior knowledge and affordance discovery, allowing to generate creative solution trajectories; (iii) an implementation of reasoning mechanisms within a neuronal substrate