The agent-based approach emphasizes the importance of learning through organism-environment interaction. This approach is part of a recent trend in computational models of learning and development toward studying autonomous organisms that are embedded in virtual or real environments. In this paper we introduce the concepts of online and offline sampling and highlight the role of online sampling in agent-based models. After comparing the strengths of each approach for modeling particular developmental phenomena and research questions, we describe a recent agent-based model of infant causal perception. We conclude by discussing some of the present limitations of agent-based models and suggesting how these challenges may be addressed. © 2001 Academic Press Computational models of learning and development are playing an increasingly critical role in child development research (Cassidy, 1990;

Developmental psychology and developmental neuropsychology have traditionally focused on the study of children. But these two fields are also supposed to be about the study of change, i.e. changes in behavior, changes in the neural structures that underlie behavior, and changes in the relationship between mind and brain across the course of development. Ironically, there has been relatively little interest in the mechanisms responsible for change in the last 15–20 years of developmental research. The reasons for this de-emphasis on change have a great deal to do with a metaphor for mind and brain that has influenced most of experimental psychology, cognitive science and neuropsychology for the last few decades, i.e. the metaphor of the serial digital computer. We will refer to this particu-

While computational models are playing an increasingly important role in developmental psychology, at least one lesson from robotics is still being learned: modeling epigenetic processes often requires simulating an embodied, autonomous organism. This paper first contrasts prevailing models of infant cognition with an agent-based approach. A series of infant studies by Baillargeon (1986; Baillargeon & DeVos, 1991) is described, and an eye-movement model is then used to simulate infants' visual activity in this study. I conclude by describing three behavioral predictions of the eyemovement model, and discussing the implications of this work for infant cognition research.

All humans, regardless of their culture and education, possess an intuitive understanding of number. Behavioural evidence suggests that numerical competence may be present early on in infancy. Here, we present brain-imaging evidence for distinct cerebral coding of number and object identity in 3-mo-old infants. We compared the visual eventrelated potentials evoked by unforeseen changes either in the identity of objects forming a set, or in the cardinal of this set. In adults and 4-y-old children, number sense relies on a dorsal system of bilateral intraparietal areas, different from the ventral occipitotemporal system sensitive to object identity. Scalp voltage topographies and cortical source modelling revealed a similar distinction in 3-mo-olds, with changes in object identity activating ventral temporal areas, whereas changes in number involved an additional right parietoprefrontal network. These results underscore the developmental continuity of number sense by pointing to early functional biases in brain organization that may channel subsequent learning to restricted brain areas. Citation: Izard V, Dehaene-Lambertz G, Dehaene S (2008) Distinct cerebral pathways for object identity and number in human infants. PLoS Biol 6(2): e11. doi:10.1371/journal. pbio.0060011

The capacity for infants to form mental representations of hidden or occluded objects can be decomposed into two tasks: one process that identifies salient objects and a second complementary process that identifies salient locations. This functional decomposition is supported by the distinction between dorsal and ventral extrastriate visual processing in the primate visual system. This approach is illustrated by presenting an eye-movement model that incorporates both dorsal and ventral processing streams and by using the model to simulate infants ’ reactions to possible and impossible events from an infant looking-time study (R. Baillargeon, “Representing the existence and the location of hidden objects: object permanence in 6- and 8-month-old infants”, Cognition, 23, pp. 21–41, 1986.). As expected, the model highlights how the dorsal system is sensitive to the location of a key feature in these events (i.e. the location of an obstacle), whereas the ventral system responds equivalently to the possible and impossible events. These results are used to help explain infants’reactions in looking-time studies. Keywords: Object representations; Dorsal–ventral model; Infant perception 1.

Abstract. Schlesinger (2003, Adaptive Behavior, 11: 97–107) recently proposed a model of eye movements as a tool for investigating infants ’ visual expectations. In the present study, this gazedirection model was evaluated by: (a) generating a set of predictions concerning how infants distribute their attention during possible and impossible events; and (b) testing these predictions in a replication of Baillargeon’s ‘car study ’ (Baillargeon, 1986, Cognition, 23: 21–41, Baillargeon and DeVos, Child Development, 62: 1227–1246). We found that the model successfully predicts general features of infants ’ gaze direction, but not specific differences obtained during the possible and impossible events. The implications of these results for infant cognition research and theory are discussed.

Smith, 1999) criticized several reports by investigators (e.g., Baillargeon, 1999; Spelke, 1998; Wynn, 1998) who offered a so-called “rich interpretation ” of findings gathered from young infants. The fundamental danger associated with such rich interpretations is that some simpler lower level mechanism may be discovered that can account for these same findings. This commentary is directed to three articles that appear in this issue of Infancy (Bogartz, Shinskey, & Schilling; Cashon & Cohen; Schilling). All three articles present empirical evidence from 4-, 5-, and 8-month-old infants that the authors contend is more consistent with a perceptually based interpretation than with the rich interpretation offered by two classic studies of object permanence in young infants (Baillargeon, 1987a; Baillargeon, Spelke, & Wasserman, 1985). I argue that the alternative explanation offered by these three sets of authors is inconsistent with both the original studies and with their own data. THE ORIGINAL “DRAWBRIDGE ” STUDIES In Baillargeon et al. (1985), 5-month-old infants were habituated to a screen that rotated 180 ° (fore and aft), much like a drawbridge. No object (other than the screen) was present during habituation, and the now-standard infant-control habituation procedure was used. Both types of test trials involved the placement of an Requests for reprints should be sent to Richard N. Aslin, Department of Brain and Cognitive Sciences,

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Robots and humans receive partial, fragmentary hints about the world’s state through their respective sensors. These hints – tiny patches of light intensity, frequency components of sound, etc. – are far removed from the world of objects we feel we perceive so effortlessly around us. The study of infant development and the construction of robots are both deeply concerned with how this apparent gap between the world and our experience of it is bridged. In this paper, we focus on some fundamental problems in perception that have attracted the attention of researchers in both robotics and infant development. Our goal is to identify points of contact already existing between the two fields, and also important questions identified in one field that could fruitfully be addressed in the other. We start with the problem of object segregation: how do infants and robots determine visually where one object ends and another begins? For object segregation, both fields have examined the idea of using “key events ” where perception is in some way simplified and the infant or robot acquires knowledge that can be exploited at other times. We propose that the identification of the key events themselves constitutes a point of contact between the fields. And although the specific algorithms used in robots do not necessarily map directly to infant strategies, the overall “algorithmic skeleton ” formed by the set of algorithms needed to identify and exploit key events may in fact form a basis for mutual dialogue. We then look more broadly at the role of embodiment in humans and robots, and see the opportunities it affords for development.

g development of the brain contribute to knowledge of development of the human mind? Will developmental neuroimaging bring new insights to developmental psychology ? I suggest an optimistic answer to this question: Developmental neuroimaging is likely to offer new insights into questions that have been central to developmental psychology for centuries. Developmental neuroimaging also may shed light on aspects of the mature human mind that have long eluded those who study adults. Before turning to this suggestion, however, I must digress and consider how neuroimaging experiments have affected the study of mature psychological processes. Neuroimaging -- particularly the functional brain imaging methods of positron emission tomography (PET), fMRI, ERP and MEG -- has swept the field of human cognitive psychology over the last decade. Its contribution to understanding human cognitive processes, however, has been uneven. When functional neuroimaging methods have probed psychological functio