Orientador: José Augusto Chaves Guimarães / Banca: Mariangela Spotti Lopes Fujita / Banca: Marcos Luiz Cavalcanti de Miranda / Resumo: Os instrumentos e os processos de representação do conhecimento refletem as visões políticas e culturais de seus idealizadores e, portanto, não são neutros. Desse modo, e considerando que a ética se estabelece como uma maneira de distanciar o poder sobre os outros, evitando ser objeto de qualquer ideologia, observa-se que, a questão da representação está intimamente ligada a uma dimensão ética, porque deve se preocupar com sua utilidade e confiabilidade para determinados grupos de usuários. Nesse sentido, propõe-se, por meio de pesquisa exploratória de natureza teórico-investigativa, estabelecer, a partir dos estudos de Antonio García Gutiérrez, Michèle Hudon e Clare Beghtol, a identificação de vertentes teóricas convergentes que subsidiem as questões sobre os aspectos éticos nas atividades de representação do conhecimento. Do cotejo e análise crítica das idéias dos referidos autores, observa-se que os mesmos possuem concepções convergentes em relação ao usuário e suas crenças, e complementares em relação à competência profissional, podendo-se concluir que os valores de transculturalidade na mediação, multilingüismo e garantia cultural são inerentes às atividades de representação do conhecimento e determinantes do fazer profissional na área. / Abstract: The instruments and the processes of knowledge representation reflect the political and cultural standpoint of its creators and, therefore, they are not neutral. That way, and considering that ethics establishes itself as a way to distance power over others, preventing itself from being the object of any ideology, one can observe that, the issue of representation is linked to an ethical dimension, because it shall concern its utility and reliability for determined groups of users. In this direction, it is considered, by means of exploratory research of theoretical-investigative character, to establish, based on the studies of Antonio García Gutiérrez, Michèle Hudon and Clare Beghtol, the identification of convergent theoretical chains that subsidize the issues on ethical aspects in the activities of knowledge representation. From confrontation and critical analysis of the ideas of the authors listed above, one can observe that the same ones have convergent takes on the user and its beliefs, and complementary takes concerning the professional ability, thus concluding that the values of transcultural ethics of mediation, multilingualism and cultural warrant are inherent to the activities of knowledge representation and determinant to professional performance in the field. / Mestre

Este estudo objetiva aproximar as Ciências Cognitivas da Semiótica Peirceana, na tentativa de compreender as dificuldades dos alunos na apropriação dos processos de representação nas disciplinas de Química Orgânica. Nesse sentido, pretende-se identificar e analisar como ocorrem os processos de percepção, interpretação e construção de representações no ensino e aprendizagem de Química Orgânica. No presente trabalho, delimitou-se a sala de aula como núcleo de uma rede de atividades para a formulação de situações de estudo. A justificativa por essa opção reside na oportunidade que esse locus fornece como meio de intercomunicação, no qual o professor apreende as participações de cada aluno em relação a um conjunto de atividades propostas ou negociadas, que são interpretadas como relações entre signos, objetos e interpretantes. Com base nos resultados da pesquisa, pode-se afirmar que a Semiótica Peirceana tem muito a contribuir na compreensão dos processos de ensino e aprendizagem de conceitos da Química Orgânica, principalmente no que se refere à importância da aquisição de sua linguagem específica no processo de elaboração conceitual. Foi possível identificar dificuldades de ensino e de aprendizagem na disciplina de Química Orgânica, mais ligadas a aspectos representacionais do que a aspectos conceituais. / This study aims to approximate the Cognitive Sciences of Peircean Semiotics, in an attempt to understand students\' difficulties in the appropriation of the processes of representation in the disciplines of Organic Chemistry. Accordingly, it is intended to identify and analyze how occur processes of perception, interpretation and construction of representations in the teaching and learning processes of Organic Chemistry contents. In this study, the classroom itself was narrowed as the core of a network of activities for the formulation of empirical situations. The rationale for this option is the opportunity that this locus provides as a means of intercommunication, where the teacher perceives the participation of each student in relation to a set of activities proposed or negotiated, which are interpreted as relations between signs, objects and interpretants. Based on the survey results, one can say that the Peircean Semiotics has much to contribute to the understanding of the processes of teaching and learning concepts of Organic Chemistry, especially with regard to language as a process of conceptual elaboration. The difficulties involved in Organic Chemistry didactics relate more to representational then to conceptual aspects.

Este estudo objetiva aproximar as Ciências Cognitivas da Semiótica Peirceana, na tentativa de compreender as dificuldades dos alunos na apropriação dos processos de representação nas disciplinas de Química Orgânica. Nesse sentido, pretende-se identificar e analisar como ocorrem os processos de percepção, interpretação e construção de representações no ensino e aprendizagem de Química Orgânica. No presente trabalho, delimitou-se a sala de aula como núcleo de uma rede de atividades para a formulação de situações de estudo. A justificativa por essa opção reside na oportunidade que esse locus fornece como meio de intercomunicação, no qual o professor apreende as participações de cada aluno em relação a um conjunto de atividades propostas ou negociadas, que são interpretadas como relações entre signos, objetos e interpretantes. Com base nos resultados da pesquisa, pode-se afirmar que a Semiótica Peirceana tem muito a contribuir na compreensão dos processos de ensino e aprendizagem de conceitos da Química Orgânica, principalmente no que se refere à importância da aquisição de sua linguagem específica no processo de elaboração conceitual. Foi possível identificar dificuldades de ensino e de aprendizagem na disciplina de Química Orgânica, mais ligadas a aspectos representacionais do que a aspectos conceituais. / This study aims to approximate the Cognitive Sciences of Peircean Semiotics, in an attempt to understand students\' difficulties in the appropriation of the processes of representation in the disciplines of Organic Chemistry. Accordingly, it is intended to identify and analyze how occur processes of perception, interpretation and construction of representations in the teaching and learning processes of Organic Chemistry contents. In this study, the classroom itself was narrowed as the core of a network of activities for the formulation of empirical situations. The rationale for this option is the opportunity that this locus provides as a means of intercommunication, where the teacher perceives the participation of each student in relation to a set of activities proposed or negotiated, which are interpreted as relations between signs, objects and interpretants. Based on the survey results, one can say that the Peircean Semiotics has much to contribute to the understanding of the processes of teaching and learning concepts of Organic Chemistry, especially with regard to language as a process of conceptual elaboration. The difficulties involved in Organic Chemistry didactics relate more to representational then to conceptual aspects.

Les technologies de l'informatique et de la robotique sont en perpétuelle évolution. S'appuyant sur cette évolution technologique, les systèmes d’aide à l’opérateur restent un domaine de recherche d’actualité. Le principal défi des systèmes de la future génération est d'être "intelligents", sensibles au contexte dans un environnement complexe et imprévisible. Cette thèse entre dans ce cadre et traite de la compréhension dynamique du contexte par un robot évoluant dans un tel environnement. En particulier, elle s'intéresse à la question suivante: comment rendre un robot capable de réagir face aux situations de blocage, imprévues dans son plan d’action initial, pour accomplir l’objectif fixé par l’opérateur ? Dans la littérature, ce problème a été soulevé et résolu en partie en programmant dans le système robotique, certaines des fonctions rendant le robot plus autonome. Cependant, l'intégration de ces fonctions dans un même cadre est manquante et plusieurs recherches dans ce sens sont en cours. Dans nos travaux nous proposons un système supportant une approche complète et générique, qui assure à un robot la capacité d’être conscient de la situation de blocage dans laquelle il se trouve et de comprendre et faire face aux situations de blocage rencontrées. Notre approche, nommée Robot Situation AWareness (RSAW) est inspirée de la notion de Situation Awareness (SA) qui a fait ses preuves dans de nombreux domaines notamment dans l’aviation. Nos principales contributions dans RSAW portent sur la conception d’un cadre sémantique intégrant la capacité de compréhension, fondé sur une représentation des connaissances générique, donnant la possibilité d’appliquer des techniques de raisonnement empruntées aux sciences cognitives. L’intégration de RSAW dans un système robotique a également été étudiée, conçue et mise en œuvre dans un système à couches. Ce système d'expérimentation est le robot SAM (Smart Autonomous Majordomo) doté du système AVISO et développé par le CEA-LIST. Les résultats des expérimentations élaborées dans le cadre des travaux menés dans cette thèse sont concluants et prometteurs / Computer technology and robotics are in perpetual evolution. Based on this technological evolution, the operator support systems remain a topical domain of research. The main challenge for the next generation of systems is to be "intelligent", aware of the context in a complex and unpredictable environment. This thesis is into this framework and addresses the dynamic understanding of the context by a robot evolving in such an environment. In particular, the work is interested in the question: How to make a robot able to react to blocked situations unplanned in its initial action plan to achieve the goal set by the operator?In the literature, this issue was raised and resolved in part by programming in robotic system, some of the features making a robot more autonomous. However, the integration of these functions in one framework is missing and more research in this direction is underway. In our work we propose a system supporting a complete and generic approach that ensures a robot the ability to be aware of the blocking situation in which it is found, to understand and deal with deadlock situations encountered. Our approach, called Robot Situation Awareness (RSAW) is inspired by the notion of Situation Awareness (SA), which has been proven in many areas especially in aviation. Our main contributions in RSAW involve the design of a semantic framework integrating the understanding capacity, based on a generic representation of knowledge and giving the possibility to apply reasoning techniques borrowed from cognitive science. Integrating RSAW in a robotic system has also been studied, designed and implemented in a layer system. This experimental system is the robot SAM (Smart Autonomous Majordomo) with the AVISO system developed by CEA-LIST. The conducted experiments allowed testing of the deductive reasoning in resolving a blocked situation and confirmed the need to resort to analogical reasoning. Another wave of experimentation has taken place to prove the effectiveness of our choices. The results of experiments developed as part of the work in this thesis are successful and promising

abstract: Knowledge Representation (KR) is one of the prominent approaches to Artificial Intelligence (AI) that is concerned with representing knowledge in a form that computer systems can utilize to solve complex problems. Answer Set Programming (ASP), based on the stable model semantics, is a widely-used KR framework that facilitates elegant and efficient representations for many problem domains that require complex reasoning. However, while ASP is effective on deterministic problem domains, it is not suitable for applications involving quantitative uncertainty, for example, those that require probabilistic reasoning. Furthermore, it is hard to utilize information that can be statistically induced from data with ASP problem modeling. This dissertation presents the language LP^MLN, which is a probabilistic extension of the stable model semantics with the concept of weighted rules, inspired by Markov Logic. An LP^MLN program defines a probability distribution over "soft" stable models, which may not satisfy all rules, but the more rules with the bigger weights they satisfy, the bigger their probabilities. LP^MLN takes advantage of both ASP and Markov Logic in a single framework, allowing representation of problems that require both logical and probabilistic reasoning in an intuitive and elaboration tolerant way. This dissertation establishes formal relations between LP^MLN and several other formalisms, discusses inference and weight learning algorithms under LP^MLN, and presents systems implementing the algorithms. LP^MLN systems can be used to compute other languages translatable into LP^MLN. The advantage of LP^MLN for probabilistic reasoning is illustrated by a probabilistic extension of the action language BC+, called pBC+, defined as a high-level notation of LP^MLN for describing transition systems. Various probabilistic reasoning about transition systems, especially probabilistic diagnosis, can be modeled in pBC+ and computed using LP^MLN systems. pBC+ is further extended with the notion of utility, through a decision-theoretic extension of LP^MLN, and related with Markov Decision Process (MDP) in terms of policy optimization problems. pBC+ can be used to represent (PO)MDP in a succinct and elaboration tolerant way, which enables planning with (PO)MDP algorithms in action domains whose description requires rich KR constructs, such as recursive definitions and indirect effects of actions. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

<div> <div> <div> <p>Researchers studying persuasion have mostly focused on modeling arguments to understand how people’s beliefs can change. However, in order to convince an audience the speakers usually adapt their speech. This can be seen often in political campaigns when ideas are phrased - framed - in different ways according to the geo-graphical region the candidate is in. This practice suggests that, in order to change people’s beliefs, it is important to take into account their previous perspectives and topics of interest. </p><p><br></p> <p>In this work we propose ChangeMyStance, a novel task to predict if a user would change their mind after being exposed to opposing views on a particular subject. This setting takes into account users’ beliefs before a debate, thus modeling their preconceived notions about the topic. Moreover, we explore a new approach to solve the problem, where the task is decomposed into ”simpler” problems. Breaking the main objective into several tasks allows to build expert modules that combined produce better results. This strategy significantly outperforms a BERT end-to-end model over the same inputs. </p> </div> </div> </div>

Knowledge representation and inference are the backbone of artificial intelligence, and logic programming is one of the most widely used knowledge representation tools. Logic programming with deduction/induction/abduction as the reasoning technique is serving numerous fields of artificial intelligence. In dynamic domains where there are constant changes in knowledge, updating the knowledge base is crucial to keep it stable. This thesis investigates the issues in updating the knowledge base. Two types of logic program based updates are considered, simple fact based updates where the knowledge base is updated by a simple fact, and rule based updates where the knowledge base is updated by a rule. A SLDNF based procedural approach is proposed to implement such updates. This thesis also investigates the issues involved in simple fact based and rule based abduction, and it is observed that updates are closely related to abduction. A SLDNF based procedural approach to perform simple fact/rule based updates and abduction is proposed as a result of this study / Master of Science (Hons)

This thesis is about logical models of belief (and knowledge) representation and belief change. This means that we propose logical systems which are intended to represent how agents perceive a situation and reason about it, and how they update their beliefs about this situation when events occur. These agents can be machines, robots, human beings. . . but they are assumed to be somehow autonomous. The way a fixed situation is perceived by agents can be represented by statements about the agents� beliefs: for example �agent A believes that the door of the room is open� or �agent A believes that her colleague is busy this afternoon�. �Logical systems� means that agents can reason about the situation and their beliefs about it: if agent A believes that her colleague is busy this afternoon then agent A infers that he will not visit her this afternoon. We moreover often assume that our situations involve several agents which interact between each other. So these agents have beliefs about the situation (such as �the door is open�) but also about the other agents� beliefs: for example agent A might believe that agent B believes that the door is open. These kinds of beliefs are called higher-order beliefs. Epistemic logic [Hintikka, 1962; Fagin et al., 1995; Meyer and van der Hoek, 1995], the logic of belief and knowledge, can capture all these phenomena and will be our main starting point to model such fixed (�static�) situations. Uncertainty can of course be expressed by beliefs and knowledge: for example agent A being uncertain whether her colleague is busy this afternoon can be expressed by �agent A does not know whether her colleague is busy this afternoon�. But we sometimes need to enrich and refine the representation of uncertainty: for example, even if agent A does not know whether her colleague is busy this afternoon, she might consider it more probable that he is actually busy. So other logics have been developed to deal more adequately with the representation of uncertainty, such as probabilistic logic, fuzzy logic or possibilistic logic, and we will refer to some of them in this thesis (see [Halpern, 2003] for a survey on reasoning about uncertainty). But things become more complex when we introduce events and change in the picture. Issues arise even if we assume that there is a single agent. Indeed, if the incoming information conveyed by the event is coherent with the agent�s beliefs then the agent can just add it to her beliefs. But if the incoming information contradicts the agent�s beliefs then the agent has somehow to revise her beliefs, and as it turns out there is no obvious way to decide what should be her resulting beliefs. Solving this problem was the goal of the logic-based belief revision theory developed by Alchourrón, Gärdenfors and Makinson (to which we will refer by the term AGM) [Alchourrón et al., 1985; Gärdenfors, 1988; Gärdenfors and Rott, 1995]. Their idea is to introduce �rationality postulates� that specify which belief revision operations can be considered as being �rational� or reasonable, and then to propose specific revision operations that fulfill these postulates. However, AGM does not consider situations where the agent might also have some uncertainty about the incoming information: for example agent A might be uncertain due to some noise whether her colleague told her that he would visit her on Tuesday or on Thursday. In this thesis we also investigate this kind of phenomenon. Things are even more complex in a multi-agent setting because the way agents update their beliefs depends not only on their beliefs about the event itself but also on their beliefs about the way the other agents perceived the event (and so about the other agents� beliefs about the event). For example, during a private announcement of a piece of information to agent A the beliefs of the other agents actually do not change because they believe nothing is actually happening; but during a public announcement all the agents� beliefs might change because they all believe that an announcement has been made. Such kind of subtleties have been dealt with in a field called dynamic epistemic logic (Gerbrandy and Groeneveld, 1997; Baltag et al., 1998; van Ditmarsch et al., 2007b]. The idea is to represent by an event model how the event is perceived by the agents and then to define a formal update mechanism that specifies how the agents update their beliefs according to this event model and their previous representaton of the situation. Finally, the issues concerning belief revision that we raised in the single agent case are still present in the multi-agent case. So this thesis is more generally about information and information change. However, we will not deal with problems of how to store information in machines or how to actually communicate information. Such problems have been dealt with in information theory [Cover and Thomas, 1991] and Kolmogorov complexity theory [Li and Vitányi, 1993]. We will just assume that such mechanisms are already available and start our investigations from there. Studying and proposing logical models for belief change and belief representation has applications in several areas. First in artificial intelligence, where machines or robots need to have a formal representation of the surrounding world (which might involve other agents), and formal mechanisms to update this representation when they receive incoming information. Such formalisms are crucial if we want to design autonomous agents, able to act autonomously in the real world or in a virtual world (such as on the internet). Indeed, the representation of the surrounding world is essential for a robot in order to reason about the world, plan actions in order to achieve goals... and it must be able to update and revise its representation of the world itself in order to cope autonomously with unexpected events. Second in game theory (and consequently in economics), where we need to model games involving several agents (players) having beliefs about the game and about the other agents� beliefs (such as agent A believes that agent B has the ace of spade, or agent A believes that agent B believes that agent A has the ace of heart...), and how they update their representation of the game when events (such as showing privately a card or putting a card on the table) occur. Third in cognitive psychology, where we need to model as accurately as possible epistemic state of human agents and the dynamics of belief and knowledge in order to explain and describe cognitive processes. The thesis is organized as follows. In Chapter 2, we first recall epistemic logic. Then we observe that representing an epistemic situation involving several agents depends very much on the modeling point of view one takes. For example, in a poker game the representation of the game will be different depending on whether the modeler is a poker player playing in the game or the card dealer who knows exactly what the players� cards are. In this thesis, we will carefully distinguish these different modeling approaches and the. different kinds of formalisms they give rise to. In fact, the interpretation of a formalism relies quite a lot on the nature of these modeling points of view. Classically, in epistemic logic, the models built are supposed to be correct and represent the situation from an external and objective point of view. We call this modeling approach the perfect external approach. In Chapter 2, we study the modeling point of view of a particular modeler-agent involved in the situation with other agents (and so having a possibly erroneous perception of the situation). We call this modeling approach the internal approach. We propose a logical formalism based on epistemic logic that this agent uses to represent �for herself� the surrounding world. We then set some formal connections between the internal approach and the (perfect) external approach. Finally we axiomatize our logical formalism and show that the resulting logic is decidable. In Chapter 3, we first recall dynamic epistemic logic as viewed by Baltag, Moss and Solecki (to which we will refer by the term BMS). Then we study in which case seriality of the accessibility relations of epistemic models is preserved during an update, first for the full updated model and then for generated submodels of the full updated model. Finally, observing that the BMS formalism follows the (perfect) external approach, we propose an internal version of it, just as we proposed an internal version of epistemic logic in Chapter 2. In Chapter 4, we still follow the internal approach and study the particular case where the event is a private announcement. We first show, thanks to our study in Chapter 3, that in a multi-agent setting, expanding in the AGM style corresponds to performing a private announcement in the BMS style. This indicates that generalizing AGM belief revision theory to a multi-agent setting amounts to study private announcement. We then generalize the AGM representation theorems to the multi-agent case. Afterwards, in the spirit of the AGM approach, we go beyond the AGM postulates and investigate multi-agent rationality postulates specific to our multi-agent setting inspired from the fact that the kind of phenomenon we study is private announcement. Finally we provide an example of revision operation that we apply to a concrete example. In Chapter 5, we follow the (perfect) external approach and enrich the BMS formalism with probabilities. This enables us to provide a fined-grained account of how human agents interpret events involving uncertainty and how they revise their beliefs. Afterwards, we review different principles for the notion of knowledge that have been proposed in the literature and show how some principles that we argue to be reasonable ones can all be captured in our rich and expressive formalism. Finally, we extend our general formalism to a multi-agent setting. In Chapter 6, we still follow the (perfect) external approach and enrich our dynamic epistemic language with converse events. This language is interpreted on structures with accessibility relations for both beliefs and events, unlike the BMS formalism where events and beliefs are not on the same formal level. Then we propose principles relating events and beliefs and provide a complete characterization, which yields a new logic EDL. Finally, we show that BMS can be translated into our new logic EDL thanks to the converse operator: this device enables us to translate the structure of the event model directly within a particular axiomatization of EDL, without having to refer to a particular event model in the language (as done in BMS). In Chapter 7 we summarize our results and give an overview of remaining technical issues and some desiderata for future directions of research. Parts of this thesis are based on publication, but we emphasize that they have been entirely rewritten in order to make this thesis an integrated whole. Sections 4.2.2 and 4.3 of Chapter 4 are based on [Aucher, 2008]. Sections 5.2, 5.3 and 5.5 of Chapter 5 are based on [Aucher, 2007]. Chapter 6 is based on [Aucher and Herzig, 2007].

Most artificial neural networks suffer from the problem of catastrophic forgetting, where previously learnt information is suddenly and completely lost when new information is learnt. Memory in real neural systems does not appear to suffer from this unusual behaviour. In this thesis we discuss the problem of catastrophic forgetting in Hopfield networks, and investigate various potential solutions. We extend the pseudorehearsal solution of Robins (1995) enabling it to work in this attractor network, and compare the results with the unlearning procedure proposed by Crick and Mitchison (1983). We then explore a familiarity measure based on the energy profile of the learnt patterns. By using the ratio of high energy to low energy parts of the network we can robustly distinguish the learnt patterns from the large number of spurious "fantasy" patterns that are common in these networks. This energy ratio measure is then used to improve the pseudorehearsal solution so that it can store 0.3N patterns in the Hopfield network, significantly more than previous proposed solutions to catastrophic forgetting. Finally, we explore links between the mechanisms investigated in this thesis and the consolidation of newly learnt material during sleep.

<p>This master's thesis deals with a frame-based knowledge representa- tion language and system called The Knowledge Machine (KM), de- veloped by Peter Clark and Bruce Porter at the University of Texas at Austin. The purpose of the thesis is to show a number of ways of changing and extending KM to handle larger classes of reasoning tasks associated with reasoning about actions and change.</p>