Project ARS (advanced recognition system) researches the future possibilities for building automation. Psychological models are used to deal with massive amounts of data in order to manage complex scenarios. Such a system would enable a building automation system to detect and comprehend situations that are too complex for existing solutions. This paper describes the motivation for this system, the impressive challenges and the first steps of implementing it. 1.

This paper addresses the relationship between social intelligence and narrative intelligence, with a particular emphasis on 1) the phylogenetic origins of primate (narrative) intelligence, and 2) the ontogenetic origin of autobiographical stories. The `Narrative Intelligence Hypothesis` (NIH) is introduced according to which the evolutionary origin of stories and narrativity was correlated with increasing social dynamics in primate societies, in particular the need to communicate about third-party relationships. Requirements for artificial socially intelligent story-tellers are outlined, and the issue of testing social intelligence is discussed.

Based on experimental findings from the study of human cognition we discuss the concept of embodiment for artifacts. We argue that embodiment is linked to a concept of a body and is not necessarily given when running a control program on robot hardware. For this purpose we introduce the concept of `body image'. Additionally, we stress the individual characteristics of an embodied cognitive system, as well as its social embeddedness. We then discuss how research on embodiment for artifacts might contribute to bridge the gap between phenomenological understanding and computationalistic approaches which traditionally dominate computer science and cognitive science. We outline a framework of the physical-psychological state-space which changes dynamically in a self-modifying way as a holistic approach towards embodied human and artificial cognition. This metapher is meant as a basis for discussion towards a common framework for cognitive architectures comprising natural and artificial sys...

Summary. – Education is a goal-oriented field. But if we want to treat education scientifically so we can accumulate, evaluate, and refine what we learn, then we must develop a theoretical framework that is strongly rooted in objective observations and through which different theoretical models of student thinking can be compared. Much that is known in the behavioral sciences is robust and observationally based. In this paper, I draw from a variety of fields ranging from neuroscience to sociolinguistics to propose an over-arching theoretical framework that allows us to both make sense of what we see in the classroom and to compare a variety of specific theoretical approaches. My synthesis is organized around an analysis of the individual’s cognition and how it interacts with the environment. This leads to a two level system, a knowledge-structure level where associational patterns dominate, and a controlstructure level where one can describe expectations and epistemology. For each level, I sketch some plausible starting models for student thinking and learning in physics and give examples of how a theoretical orientation can affect instruction and research. 1