Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to “switch” between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage-wise (...) development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture embodied on the iCub humanoid robot, exhibits ongoing multi-stage development while learning pre-linguistic and then basic language skills. (shrink)

This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these (...) capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots. (shrink)

It is well-established that toddlers can correctly select a novel referent from an ambiguous array in response to a novel label. There is also a growing consensus that robust word learning requires repeated label-object encounters. However, the effect of the context in which a novel object is encountered is less well-understood. We present two embodied neural network replications of recent empirical tasks, which demonstrated that the context in which a target object is encountered is fundamental to referent selection and word (...) learning. Our model offers an explicit account of the bottom-up associative and embodied mechanisms which could support children’s early word learning and emphasises the importance of viewing behaviour as the interaction of learning at multiple timescales. (shrink)

Although work on computational and robotic modelling of cognition is highly diverse, as an empirical method it can be roughly divided into at least two clearly different, though non-exclusive branches, motivated to evaluate the sufficiency or the necessity of theories when it comes to accounting for data and/or other observations. With the rising profile of theories of situated/embodied cognition, a third non-exclusive avenue for investigation has also gained in popularity, the investigation of agent-environment embedding or more generally, exploration. Still in (...) its infancy, and often confused with sufficiency testing, this relatively new kind of modelling, which is theory- rather than data-driven, investigates the role of the environment in shaping the ontogenetic and/or phylogenetic development of situated agency. Each of these three approaches presents many issues that modellers must be sensitive to, both in the design of experiments, and in the conclusions that can be drawn from them. This paper highlights some of these issues, provides examples, and addresses the contribution of computational/robotic modelling to cognitive science, as well as some of its limitations. (shrink)

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Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to “switch” between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage‐wise (...) development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture (Morse et al 2010) embodied on the iCub humanoid robot, exhibits ongoing multi‐stage development while learning pre‐linguistic and then basic language skills. (shrink)

Understanding the relationship between concepts and experience seems necessary to specifying the content of experience, yet current theories of concepts do not seem up to the job. With Peter Gärdenfors's conceptual spaces theory as a foundation and with enactivist philosophy as inspiration, we present a proposed extension to conceptual spaces theory and use it to outline a model of the emergence of concepts and experience. We conclude that neither is ultimately primary but each gives rise to the other: i.e., that (...) they co-emerge. Such a model can then serve as the anchor to a theory of concepts more generally. Concepts are most naturally understood in symbolic and representational terms, while much of experience, in contrast, is non-symbolic and non-representational; yet the conflict between the two will, herein, be shown to be more apparent than real. The main contribution of this paper is to argue for, by means of this account of co-emergence, a continuum between "low-level" mental content that is more appropriately understood in highly context-sensitive and directly sensorimotor-based terms, and "high-level" mental content that is more appropriately understood in context-free and representational or symbolic terms. In doing so we conclude that the extreme positions of representationalism and anti-representationalism are fatally flawed. (shrink)

The author reflects on the premature speculations of many commentators on robot caregivers. He argues on the commentator's ethical issues that it creates false beliefs in children, in which he says that the creation of false beliefs by their caretakers is part and parcel of childhood. He argues that societies are already delegated the childcare onto others such as school and since technology is often substituting for direct physical social contact, its time to embrace the robotic care.