Building Brains for Bodies

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to "think'' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience

Intelligent Adaptive Curiosity: a source of Self-Development

This paper presents the mechanism of Intelligent Adaptive Curiosity. This is a drive which pushes the robot towards situations in which it maximizes its learning progress. It makes the robot focus on situations which are neither too predictable nor too unpredictable. This mechanism is a source of self-development for the robot: the complexity of its activity autonomously increases. Indeed, we show that it first spends time in situations which are easy to learn, then shifts progressively its attention to situations of increasing difficulty, avoiding situations in which nothing can be learnt

Cog and the Creativity of God

The construction of a humanoid robot may be within reach. The science of artificial intelligence (AI) offers new understandings to contemporary Christian theology. First of all, the emerging field of embodied intelligence discloses the wholeness of the human being, correcting the tendency in Christian theology toward an anthropological dualism of body and soul. Secondly, artificial intelligence offers fresh understandings of the human mind, with implications for how human creativity reflects the creativity of God

Social Situatedness: Vygotsky and Beyond

The concept of ‘social situatedness’, i.e. the idea that the development of individual intelligence requires a social (and cultural) embedding, has recently received much attention in cognitive science and artificial intelligence research. The work of Lev Vygotsky who put forward this view already in the 1920s has influenced the discussion to some degree, but still remains far from well known. This paper therefore aims to give an overview of his cognitive development theory and discuss its relation to more recent work in primatology and socially situated artificial intelligence, in particular humanoid robotics

An autonomous robot that learns approach-avoidance behaviors: lessons from the brain to the robot

This is an electronic version of the paper presented at the I Jornadas Técnicas de la ETS de Informática, held in Madrid on 200

Knowledge-based vision and simple visual machines

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

La Crítica Antirepresentacionalista en la Ciencia Cognitiva Corporizada

La noción de representación mental (RM) ha sido objeto de un extraordinario escrutinio, sin considerar además los densos problemas filosóficos y semánticos que han sido generados a su alrededor Pocos conceptos en las ciencias cognitivas han traído, y continúan trayendo, tanta discusión, y con ella tanto malentendido y confusión, como éste. Esto se debe en parte a que en la literatura dicho concepto es utilizado en una desorientadora variedad de maneras. La ubicuidad de la noción en cuestión puede quizás parecer loable en tanto que ofrece un plano intuitivo común de discusión posibilitando, dentro del campo heterogéneo que caracteriza las ciencias cognitivas, el diálogo entre disciplinas muy dispares Podría incluso hipotetizarse que es justamente como resultado de esta característica que la noción ha mantenido su estatus como término técnico casi inderogable. Sea como fuere, existe por otra parte una vasta y creciente literatura que pareciera relegar a un segundo plano y, según alegan algunos, inclusive descartar, la noción de RM Esta maniobra forma parte de un alejamiento más general respecto de ciertos enfoques investigativos tradicionales, protagonizado por un reciente conjunto de estudios multidisciplinares denominado "ciencia cognitiva corporizada''