Abstract not found

If we are to build human-like robots that can interact naturally with people, our robots must know not only about the properties of objects but also the properties of animate agents in the world. One of the fundamental social skills for humans is the attribution of beliefs, goals, and desires to other people. This set of skills has often been called a “theory of mind.” This paper presents the theories of Leslie (1994) and Baron-Cohen (1995) on the development of theory of mind in human children and discusses the potential application of both of these theories to building robots with similar capabilities. Initial implementation details and basic skills (such as finding faces and eyes and distinguishing animate from inanimate stimuli) are introduced. I further speculate on the usefulness of a robotic implementation in evaluating and comparing these two models.

The evolution of language implies the parallel evolution of an ability to respond appropriately to signals (language understanding) and an ability to produce the appropriate signals in the appropriate circumstances (language production). When linguistic signals are produced to inform other individuals, individuals that respond appropriately to these signals may increase their reproductive chances but it is less clear what is the reproductive advantage for the languages producers. We present simulations in which populations of neural networks living in an environment evolve a simple language with an informative function. Signals are produced to help other individuals to categorize edible and poisonous mushrooms in order to decide whether to approach or avoid encountered mushrooms. Language production, while not under direct evolutionary pressure, evolves as a by-product of the independently evolving perceptual ability to categorize mushrooms. Keywords: Language evolution, Ge...

Abstract. Adults are extremely adept at recognizing social cues, such as eye direction or pointing gestures, that establish the basis of joint attention. These skills serve as the developmental basis for more complex forms of metaphor and analogy by allowing an infant to ground shared experiences and by assisting in the development of more complex communication skills. In this chapter, we review some of the evidence for the developmental course of these joint attention skills from developmental psychology, from disorders of social development such as autism, and from the evolutionary development of these social skills. We also describe an on-going research program aimed at testing existing models of joint attention development by building a human-like robot which communicates naturally with humans using joint attention. Our group has constructed an upper-torso humanoid robot, called Cog, in part to investigate how to build intelligent robotic systems by following a developmental progression of skills similar to that observed in human development. Just as a child learns social skills and conventions through interactions with its parents, our robot will learn to interact with people using natural social communication. We further consider the critical role that imitation plays in bootstrapping a system from simple visual behaviors to more complex social skills. We will present data from a face and eye finding system that serves as the basis of this developmental chain, and an example of how this system can imitate the head movements of an individual. 1

This paper presents an implemented computational model of lexical development for the case of action verbs. A simulated agent is trained by an informant giving labels to the agent's actions (here hand motions) and the system learns to both label and carry out similar actions. Computationally, the system employs a novel form of active representation and is explicitly intended to be neurally plausible. The learning methodology is a version of Bayesian model merging (Omohundro, 1992). The verb learning model is placed in the broader context of the L0 project on embodied natural language and its acquisition.

The evaluation of models of social and behavioral development is difficult in natural settings; ethical concerns, difficulties in implementing experimental procedures, and difficulties in isolating hypothesized variables make experimental evidence difficult or impossible to obtain. We propose the use of human-like robots as a testbed for the evaluation of models of human social development. Robotic implementation of human social models allows for unique opportunities to evaluate those models. In this paper, we review some of the implications of this proposal by examining a case study of an on-going project to implement an existing model of one aspect human social development, the development of joint attention behaviors.

This paper describes different types of models for the evolution of communication and language. It uses the distinction between signals, symbols, and words for the analysis of evolutionary models of language. In particular, it show how evolutionary computation techniques, such as Artificial Life, can be used to study the emergence of syntax and symbols from simple communication signals. Initially, a computational model that evolves repertoires of isolated signals is presented. This study has simulated the emergence of signals for naming foods in a population of foragers. This type of model studies communication systems based on simple signal-object associations. Subsequently, models that study the emergence of grounded symbols are discussed in general, including a detailed description of a work on the evolution of simple syntactic rules. This model focuses on the emergence of symbol-symbol relationships in evolved languages. Finally, computational models of syntax acquisition and evolution are discussed. These different types of computational models provide an operational def'mition of the signal/symbol/word distinction. The simulation and analysis of these types of models will help understanding the role of symbols and symbol acquisition in the origin of language.

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This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply `pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively.

The article analyzes the neural and functional grounding of language skills as well as their emergence in hominid evolution, hypothesizing stages leading from abilities known to exist in monkeys and apes and presumed to exist in our hominid ancestors right through to modern spoken and signed languages. The starting point is the observation that both premotor area F5 in monkeys and Broca's area in humans contain a "mirror system" active for both execution and observation of manual actions, and that F5 and Broca's area are homologous brain regions. This grounded the mirror system hypothesis of Rizzolatti and Arbib (1998) which offers the mirror system for grasping as a key neural "missing link" between the abilities of our nonhuman ancestors of 20 million years ago and modern human language, with manual gestures rather than a system for vocal communication providing the initial seed for this evolutionary process. The present article, however, goes "beyond the mirror" to offer hypotheses on evolutionary changes within and outside the mirror systems which may have occurred to equip Homo sapiens with a language-ready brain. Crucial to the early stages of this progression is the mirror system for grasping and its extension to permit imitation. Imitation is seen as evolving via a so-called simple system such as that found in chimpanzees (which allows imitation of complex "object-oriented" sequences but only as the result of extensive practice) to a so-called complex system found in humans (which allows rapid imitation even of complex sequences, under appropriate conditions) which supports pantomime. This is hypothesized to have provided the substrate for the development of protosign, a combinatorially open repertoire of manual gestures, which then provides the scaffolding for the emergence of protospeech (which thus owes little to nonhuman vocalizations), with protosign and protospeech then developing in an expanding spiral. It is argued that these stages involve biological evolution of both brain and body. By contrast, it is argued that the progression from protosign and protospeech to languages with full-blown syntax and compositional semantics was a historical phenomenon in the development of Homo sapiens, involving few if any further biological changes.