Robo-CAMAL : anchoring in a cognitive robot

The CAMAL architecture (Computational Architectures for Motivation,Affect and Learning) provides an excellent framework within which to explore and investigate issues relevant to cognitive science and artificial intelligence. This thesis describes a small sub element of the CAMAL architecture that has been implemented on a mobile robot. The first area of investigation within this research relates to the anchoring problem. Can the robotic agent generate symbols based on responses within its perceptual systems and can it reason about its environment based on those symbols? Given that the agent can identify changes within its environment, can it then adapt its behaviour and alter its goals to mirror the change in its environment? The second area of interest involves agent learning. The agent has a domain model that details its goals, the actions it can perform and some of the possible environmental states it may encounter. The agent is not provided with the belief-goal-action combinations in order to achieve its goals. The agent is also unaware of the effect its actions have upon its environment. Can the agent experiment with its behaviour to generate its own belief-goal-action combinations that allow it to achieve its goals? A second related problem involves the case where the belief-goal-action combination is pre-programmed. This is when the agent is provided with several different methods with which to achieve a specific goal. Can the agent learn which combination is the best? This thesis will describe the sub-element of the CAMAL architecture that was developed for a robot (robo-CAMAL). It will also demonstrate how robo-CAMAL solves the anchoring problem, and learns how to act and adapt in its environment

Grounding the Interaction : Knowledge Management for Interactive Robots

Avec le développement de la robotique cognitive, le besoin d’outils avancés pour représenter, manipuler, raisonner sur les connaissances acquises par un robot a clairement été mis en avant. Mais stocker et manipuler des connaissances requiert tout d’abord d’éclaircir ce que l’on nomme connaissance pour un robot, et comment celle-ci peut-elle être représentée de manière intelligible pour une machine. \ud \ud Ce travail s’efforce dans un premier temps d’identifier de manière systématique les besoins en terme de représentation de connaissance des applications robotiques modernes, dans le contexte spécifique de la robotique de service et des interactions homme-robot. Nous proposons une typologie originale des caractéristiques souhaitables des systèmes de représentation des connaissances, appuyée sur un état de l’art détaillé des outils existants dans notre communauté. \ud \ud Dans un second temps, nous présentons en profondeur ORO, une instanciation particulière d’un système de représentation et manipulation des connaissances, conçu et implémenté durant la préparation de cette thèse. Nous détaillons le fonctionnement interne du système, ainsi que son intégration dans plusieurs architectures robotiques complètes. Un éclairage particulier est donné sur la modélisation de la prise de perspective dans le contexte de l’interaction, et de son interprétation en terme de théorie de l’esprit. \ud \ud La troisième partie de l’étude porte sur une application importante des systèmes de représentation des connaissances dans ce contexte de l’interaction homme-robot : le traitement du dialogue situé. Notre approche et les algorithmes qui amènent à l’ancrage interactif de la communication verbale non contrainte sont présentés, suivis de plusieurs expériences menées au Laboratoire d’Analyse et d’Architecture des Systèmes au CNRS à Toulouse, et au groupe Intelligent Autonomous System de l’université technique de Munich. Nous concluons cette thèse sur un certain nombre de considérations sur la viabilité et l’importance d’une gestion explicite des connaissances des agents, ainsi que par une réflexion sur les éléments encore manquant pour réaliser le programme d’une robotique “de niveau humain”.-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------With the rise of the so-called cognitive robotics, the need of advanced tools to store, manipulate, reason about the knowledge acquired by the robot has been made clear. But storing and manipulating knowledge requires first to understand what the knowledge itself means to the robot and how to represent it in a machine-processable way. \ud \ud This work strives first at providing a systematic study of the knowledge requirements of modern robotic applications in the context of service robotics and human-robot interaction. What are the expressiveness requirement for a robot? what are its needs in term of reasoning techniques? what are the requirement on the robot's knowledge processing structure induced by other cognitive functions like perception or decision making? We propose a novel typology of desirable features for knowledge representation systems supported by an extensive review of existing tools in our community. \ud \ud In a second part, the thesis presents in depth a particular instantiation of a knowledge representation and manipulation system called ORO, that has been designed and implemented during the preparation of the thesis. We elaborate on the inner working of this system, as well as its integration into several complete robot control stacks. A particular focus is given to the modelling of agent-dependent symbolic perspectives and their relations to theories of mind. \ud \ud The third part of the study is focused on the presentation of one important application of knowledge representation systems in the human-robot interaction context: situated dialogue. Our approach and associated algorithms leading to the interactive grounding of unconstrained verbal communication are presented, followed by several experiments that have taken place both at the Laboratoire d'Analyse et d'Architecture des Systèmes at CNRS, Toulouse and at the Intelligent Autonomous System group at Munich Technical University. \ud \ud The thesis concludes on considerations regarding the viability and importance of an explicit management of the agent's knowledge, along with a reflection on the missing bricks in our research community on the way towards "human level robots". \ud \u

Embodied Cognitive Science of Music. Modeling Experience and Behavior in Musical Contexts

Recently, the role of corporeal interaction has gained wide recognition within cognitive musicology. This thesis reviews evidence from different directions in music research supporting the importance of body-based processes for the understanding of music-related experience and behaviour. Stressing the synthetic focus of cognitive science, cognitive science of music is discussed as a modeling approach that takes these processes into account and may theoretically be embedded within the theory of dynamic systems. In particular, arguments are presented for the use of robotic devices as tools for the investigation of processes underlying human music-related capabilities (musical robotics)

Anchoring Symbols to Percepts in the Fluent Calculus

An abstract knowledge representation of cognitive robots - as used for reasoning and planning - typically relies on symbols denoting objects of the world and states of affairs. The process of creating and maintaining the correct connection between a symbol denoting an object and its corresponding perceptual image (called percept), both referring to the same physical object, is called symbol anchoring. Most current cognitive systems implement an ad hoc solution which may work for the specific, intended application under certain conditions. Conversely, we suggest a formal and general approach to the symbol anchoring problem, which enhances previous approaches in terms of flexibility, applicability and expressiveness, and which completely automates the process of determining and maintaining all plausible hypotheses of correspondences between object symbols and perceptual images of physical objects. Based on the first-order logical Fluent Calculus, our approach inherits its rich expressiveness with respect to knowledge representation and reasoning. Implementing all required symbol anchoring functionalities, our approach also complies with fundamental concepts of phenomenalism, representationalism and the sense-data theory of philosophy of cognition

Living in a natural world

Die Dissertation besteht aus drei Teilen: der erste behandelt Rationalität und deren Bedeutung für alle Fragen des Lebens, nicht nur für einen reduzierten – für wissenschaftliche Untersuchungen reservierten – Teilbereich der Welt; der zweite Teil ist metaphysischer Natur und skizziert den postulierten Aufbau der Welt anhand der im ersten Teil erläuterten Prinzipien. Im dritten Teil frage ich – und gebe vorläufige Antworten – wie die Ergebnisse der vorherigen Teile unseren Blickwinkel auf empfindsame Wesen des Universums – darunter Menschen – ändern. Nur wenn wir rational sind können wir das Maximum an Information aus unserer Umwelt extrahieren. Unser beste Weg zum Erkenntnisgewinn sollte auch Leitfaden für unsere Spiritualität, Ethik, unsere Ansichten über den Sinn des Lebens etc sein. Es ist wichtig die sich mit unserem Erkenntnisstand ändernden Standards der Rationalität auf alle menschlichen Unterfangen anzuwenden. Für Individuen bedeutet Wissen gute mentale Modelle der Welt zu besitzen: je genauer effektive Faktoren in der Welt gespiegelt werden, umso besser können angestrebte Ziele erreicht werden. Unwissenheit führt zu Inaktivität und Passivität. Die Bewährungsprobe für Wissen und Philosophie ist die: werden durch sie die Art und Weise wie wir die Welt, unser Leben, und – letztlich am Wichtigsten – die Art und Weise wie wir handeln, verändert?The thesis consists of three parts: the first being on rationality and its import in tackling all questions facing us in our lives, not only a reduced domain of scientific investigation; the second, metaphysical in nature, forming an essay on the nature of the world, especially as informed by the principles of rationality sketched in the previous part; and the third, applying the findings of the previous sections to sentient agents – among them humans – in this universe. I argue that the rational approach is the best way to approach all questions facing us in our lives. Only by being rational can we extract as much information from our environment as possible. Our best way of gaining knowledge should quite naturally also influence our spirituality, our ethics, our view of the meaning of life and so on. It is important to apply the open standards of rationality to all areas of interest to humans. The agent centric approach is central to the thesis. For individuals, knowledge means having a good mental model of the world: the closer to the actual effective factors in the world, the more potential there is for action leading to achievement of goals. Ignorance condemns one to inaction and passivity. The litmus test for knowledge – and philosophy – is this: does it change the way we view the world, our life, and, ultimately and most importantly, the way we act