The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate “causal map ” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

Abstract not found

The identification of any form of social learning, imitation, copying or mimicry presupposes a notion of correspondence between two autonomous agents. Judging whether a behavior has been transmitted socially requires the observer to identify a mapping between the demonstrator and the imitator. If the demonstrator and imitator have similar bodies, e.g. are animals of the same species, of similar age, and of the same gender, then to a human observer an obvious correspondence is to map the corresponding body parts: left arm of demonstrator maps to left arm of imitator, right eye of demonstrator maps to right eye of imitator, tail of demonstrator maps to tail of imitator. There is also an obvious correspondence of actions: raising the left arm by the model corresponds to raising the left arm by the imitator, production of vocal signals by the model corresponds to the production of acoustically similar ones by the imitator, picking up a fruit by the demonstrator corresponds to picking up a fruit of the same type by the imitator. Furthermore, there is a correspondence in sensory experience: audible sounds, a touch, visible objects and colors, and so on evidently seem to be detected and experienced in similar ways. What to take as the correspondence seems relatively clear in this case. As humans, we are good at imitating and at recognizing such correspondences. It is also clear that most other animals, robots, and software programs may in fact generally fail to recognize any such correspondences. To judge a produced behavior to be a copy of an observed one, we require at least that it respects some such correspondence. The faithfulness or precision of the behavioral match can obviously vary, and no absolute cutoff or threshold exists defining success as opposed to failure of behavioral matching. But one can study the degree of success using various metrics and measures of correspondence (Nehaniv & Dautenhahn, 2001; also see below). Moreover, it turns out that the “obvious” correspondences between similar bodies mentioned above are not the only ones possible. Consider a human imitating another one that is facing her: if the demonstrator raises her left arm, should the imitator raise her own left arm? Or should she raise her right, to make a "mirror image" of the demonstrator's actions? If the demonstrator picks up a brush, should an imitator pick up the same brush? Or just another brush of the same type? If the demonstrator opens a container to get at chocolate inside, should the imitator open a similar container in the same way – e.g. by unwrapping but not tearing the surrounding paper?, or is it enough just to open the container somehow? The different possible answers to these questions presuppose different correspondences. If a child watches a teacher solving subtraction problems in arithmetic, and then solves for the first time similar but not identical problems on its own, social learning has occurred. But what type of correspondence is at work here? In China and Japan, the ideographic character for “to imitate” also means “to learn” or “to study”. By going through the motions of an algorithm for solving sample problems, students everywhere are able to learn how to solve similar ones, of course without necessarily gaining understanding of why the procedures they have learned work. In this chapter, for lack of a better term, we shall use the word “imitator” to refer to any autonomous agent performing a candidate behavioral match. The use of this word here does not entail any particular mechanism of matching or any particular type of social learning. In what follows, we shall describe how different matching phenomena arise depending on the criteria employed in generating the behavior of the imitator. For example, goal emulation, stimulus enhancement, mimicry, and so on, will all be cast as solutions to correspondence problems with different particular selection criteria.

Introduction This chapter presents the agent-based perspective on imitation. In this perspective, imitation is best considered as the behavior of an autonomous agent in relation to its environment, including other autonomous agents. We argue that such a perspective helps unfold the full potential of research on imitation and helps in identifying challenging and important research issues. We first explain the agent-based perspective and then discuss it in the context of particular research issues in studies with animals and artifacts, with reference to chapters presented in this book. At the end of the chapter we briefly introduce the individual contributions to this book and provide a roadmap that helps the reader in navigating through the exciting and highly interwoven themes that are presented in this book. In order to focus discussions, we explain the agent-based perspective with particular consideration of the correspondence

Learning through imitation is a powerful and versatile method for acquiring new behaviors. In humans, a wide range of behaviors, from styles of social interaction to tool use, are passed from one generation to another through imitative learning. Although imitation evolved through Darwinian means, it achieves Lamarckian ends: it is a mechanism for the inheritance of acquired characteristics. Unlike trial-and-error-based learning methods such as reinforcement learning, imitation allows rapid learning.

Human language is unique among the communication systems of the natural world. The vocabulary of human language is unique in being both culturally-transmitted and symbolic. In this paper I present an investigation into the factors involved in the evolution of such vocabulary systems. I investigate both the cultural evolution of vocabulary systems and the biological evolution of learning rules for vocabulary acquisition.

What are the brain and cognitive systems that allow humans to play baseball, compute square roots, cook soufflés, or navigate the Tokyo subways? It may seem that studies of human infants and of non-human animals will tell us little about these abilities, because only educated, enculturated human adults engage in organized games, formal mathematics, gourmet cooking, or map-reading. In this chapter, we argue against this seemingly sensible conclusion. When human adults exhibit complex, uniquely human, culture-specific skills, they draw on a set of psychological and neural mechanisms with two distinctive properties: they evolved before humanity and thus are shared with other animals, and they emerge early in human development and thus are common to infants, children, and adults. These core knowledge systems form the building blocks for uniquely human skills. Without them we wouldn’t be able to learn about different kinds of games, mathematics, cooking, or maps. To understand what is special about human intelligence, therefore, we must study both the core knowledge systems on which it rests and the mechanisms by which these systems are orchestrated to permit new kinds of concepts and cognitive processes. What is core knowledge? A wealth of research on non-human primates and on human

Abstract not found

this article should be addressed to Jay Pratt, Department of Psychology, University of Toronto, 100 Saint George Street, Toronto, Ontario M5S 3G3, Canada. E-mail: pratt@psych .utoronto.ca Journal of Experimental Psychology: Copyright 2003 by the American Psychological Association, Inc. Human Perception and Performance 2003, Vol. 29, No. 5, 835--845 0096-1523/03/$12.00 DOI: 10.1037/0096-1523.29.5.835 835 Recently, Hommel, Pratt, Colzato, and Godijn (2001) showed that involuntary shifts of attention are not limited to viewing hand or eye movements but also occur with simple, overlearned communicative symbols. Hommel et al. presented centrally located arrows and directional words (up, down, left, right) which were followed by a peripheral target. It is important to note that these symbols were entirely irrelevant to the task, and the observers were explicitly told that arrows and words contained no useful information about the location of the upcoming target. Nevertheless, in the first and third experiments, targets were detected faster when they occurred at the location indicated by the arrow or word (compatible condition) than at another location (incompatible condition). The second experiment extended this finding by showing that the compatibility effect also affected (i.e., counteracted) inhibition of return (IOR), a long-lasting attentional inhibitory effect. Finally, the fourth experiment showed that the compatibility effect was present even when the observers were told which location was the most likely target location. Thus, even in the presence of a volitional shift of attention to a specific location, the noninformative arrows and directional words still influenced the responses. Moreover, the compatibility effects occurred for targets at both the volitionall...

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.