Motivations, Values and Emotions: 3 sides of the same coin

This position paper speaks to the interrelationships between the three concepts of motivations, values, and emotion. Motivations prime actions, values serve to choose between motivations, emotions provide a common currency for values, and emotions implement motivations. While conceptually distinct, the three are so pragmatically intertwined as to differ primarily from our taking different points of view. To make these points more transparent, we briefly describe the three in the context a cognitive architecture, the LIDA model, for software agents and robots that models human cognition, including a developmental period. We also compare the LIDA model with other models of cognition, some involving learning and emotions. Finally, we conclude that artificial emotions will prove most valuable as implementers of motivations in situations requiring learning and development

A Cognitive Science Based Machine Learning Architecture

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, humanlike learning mechanisms:\ud 1) perceptual learning, the learning of new objects, categories, relations, etc.,\ud 2) episodic learning of events, the what, where, and when,\ud 3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence

A Biosymtic (Biosymbiotic Robotic) Approach to Human Development and Evolution. The Echo of the Universe.

In the present work we demonstrate that the current Child-Computer Interaction paradigm is not potentiating human development to its fullest – it is associated with several physical and mental health problems and appears not to be maximizing children’s cognitive performance and cognitive development. In order to potentiate children’s physical and mental health (including cognitive performance and cognitive development) we have developed a new approach to human development and evolution. This approach proposes a particular synergy between the developing human body, computing machines and natural environments. It emphasizes that children should be encouraged to interact with challenging physical environments offering multiple possibilities for sensory stimulation and increasing physical and mental stress to the organism. We created and tested a new set of computing devices in order to operationalize our approach – Biosymtic (Biosymbiotic Robotic) devices: “Albert” and “Cratus”. In two initial studies we were able to observe that the main goal of our approach is being achieved. We observed that, interaction with the Biosymtic device “Albert”, in a natural environment, managed to trigger a different neurophysiological response (increases in sustained attention levels) and tended to optimize episodic memory performance in children, compared to interaction with a sedentary screen-based computing device, in an artificially controlled environment (indoors) - thus a promising solution to promote cognitive performance/development; and that interaction with the Biosymtic device “Cratus”, in a natural environment, instilled vigorous physical activity levels in children - thus a promising solution to promote physical and mental health

Méthodes d'apprentissage inspirées de l'humain pour un tuteur cognitif artificiel

Les systèmes tuteurs intelligents sont considérés comme un remarquable concentré de technologies qui permettent un processus d'apprentissage. Ces systèmes sont capables de jouer le rôle d'assistants voire même de tuteur humain. Afin d'y arriver, ces systèmes ont besoin de maintenir et d'utiliser une représentation interne de l'environnement. Ainsi, ils peuvent tenir compte des évènements passés et présents ainsi que de certains aspects socioculturels. Parallèlement à l'évolution dynamique de l'environnement, un agent STI doit évoluer en modifiant ses structures et en ajoutant de nouveaux phénomènes. Cette importante capacité d'adaptation est observée dans le cas de tuteurs humains. Les humains sont capables de gérer toutes ces complexités à l'aide de l'attention et du mécanisme de conscience (Baars B. J., 1983, 1988), et (Sloman, A and Chrisley, R., 2003). Toutefois, reconstruire et implémenter des capacités humaines dans un agent artificiel est loin des possibilités actuelles de la connaissance de même que des machines les plus sophistiquées. Pour réaliser un comportement humanoïde dans une machine, ou simplement pour mieux comprendre l'adaptabilité et la souplesse humaine, nous avons à développer un mécanisme d'apprentissage proche de celui de l'homme. Ce présent travail décrit quelques concepts d'apprentissage fondamentaux implémentés dans un agent cognitif autonome, nommé CTS (Conscious Tutoring System) développé dans le GDAC (Dubois, D., 2007). Nous proposons un modèle qui étend un apprentissage conscient et inconscient afin d'accroître l'autonomie de l'agent dans un environnement changeant ainsi que d'améliorer sa finesse. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Apprentissage, Conscience, Agent cognitif, Codelet

Autonomous decision-making for socially interactive robots

Mención Internacional en el título de doctorThe aim of this thesis is to present a novel decision-making system based on bio-inspired concepts to decide the actions to make during the interaction between humans and robots. We use concepts from nature to make the robot may behave analogously to a living being for a better acceptance by people. The system is applied to autonomous Socially Interactive Robots that works in environments with users. These objectives are motivated by the need of having robots collaborating, entertaining or helping in educational tasks for real situations with children or elder people where the robot has to behave socially. Moreover, the decision-making system can be integrated into this kind of robots in order to learn how to act depending on the user profile the robot is interacting with. The decision-making system proposed in this thesis is a solution to all these issues in addition to a complement for interactive learning in HRI. We also show real applications of the system proposed applying it in an educational scenario, a situation where the robot can learn and interact with different kinds of people. The last goal of this thesis is to develop a robotic architecture that is able to learn how to behave in different contexts where humans and robots coexist. For that purpose, we design a modular and portable robotic architecture that is included in several robots. Including well-known software engineering techniques together with innovative agile software development procedures that produces an easily extensible architecture.El objetivo de esta tesis es presentar un novedoso sistema de toma de decisiones basado en conceptos bioinspirados para decidir las acciones a realizar durante la interacción entre personas y robots. Usamos conceptos de la naturaleza para hacer que el robot pueda comportarse análogamente a un ser vivo para una mejor aceptación por las personas. El sistema está desarrollado para que se pueda aplicar a los llamados Robots Socialmente Interactivos que están destinados a entornos con usuarios. Estos objetivos están motivados por la necesidad de tener robots en tareas de colaboración, entretenimiento o en educación en situaciones reales con niños o personas mayores en las cuales el robot debe comportarse siguiendo las normas sociales. Además, el sistema de toma de decisiones es integrado en estos tipos de robots con el fin de que pueda aprender a actuar dependiendo del perfil de usuario con el que el robot está interactuando. El sistema de toma de decisiones que proponemos en esta tesis es una solución a todos estos desafíos además de un complemento para el aprendizaje interactivo en la interacción humano-robot. También mostramos aplicaciones reales del sistema propuesto aplicándolo en un escenario educativo, una situación en la que el robot puede aprender e interaccionar con diferentes tipos de personas. El último objetivo de esta tesis es desarrollar un arquitectura robótica que sea capaz de aprender a comportarse en diferentes contextos donde las personas y los robots coexistan. Con ese propósito, diseñamos una arquitectura robótica modular y portable que está incluida en varios robots. Incluyendo técnicas bien conocidas de ingeniería del software junto con procedimientos innovadores de desarrollo de sofware ágil que producen una arquitectura fácilmente extensible.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Fabio Bonsignorio.- Secretario: María Dolores Blanco Rojas.- Vocal: Martin Stoele

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

The Role of Consciousness in Memory

Conscious events interact with memory systems in learning, rehearsal and retrieval (Ebbinghaus 1885/1964; Tulving 1985). Here we present hypotheses that arise from the IDA computional model (Franklin, Kelemen and McCauley 1998; Franklin 2001b) of global workspace theory (Baars 1988, 2002). Our primary tool for this exploration is a flexible cognitive cycle employed by the IDA computational model and hypothesized to be a basic element of human cognitive processing. Since cognitive cycles are hypothesized to occur five to ten times a second and include interaction between conscious contents and several of the memory systems, they provide the means for an exceptionally fine-grained analysis of various cognitive tasks. We apply this tool to the small effect size of subliminal learning compared to supraliminal learning, to process dissociation, to implicit learning, to recognition vs. recall, and to the availability heuristic in recall. The IDA model elucidates the role of consciousness in the updating of perceptual memory, transient episodic memory, and procedural memory. In most cases, memory is hypothesized to interact with conscious events for its normal functioning. The methodology of the paper is unusual in that the hypotheses and explanations presented are derived from an empirically based, but broad and qualitative computational model of human cognition