A Developmental Approach For Affordance And Imitation Learning Through Self Exploration In Cognitive Robots PDF Download

Mastering the sensorimotor capabilities of our body is a skill that we acquire and refine over time, starting at the prenatal stages of development. This learning process is linked to brain development and is shaped by the rich set of multimodal information experienced while exploring and interacting with the environment. Evidence coming from neuroscience suggests the brain forms and mantains body representations as the main strategy to this mastering. Although it is still not clear how this knowledge is represented in our brain, it is reasonable to think that such internal models of the body undergo a continuous process of adaptation. They need to match growing corporal dimensions during development, as well as temporary changes in the characteristics of the body, such as the transient morphological alterations produced by the usage of tools. In the robotics community there is an increasing interest in reproducing similar mechanisms in artificial agents, mainly motivated by the aim of producing autonomous adaptive systems that can deal with complexity and uncertainty in human environments. Although promising results have been achieved in the context of sensorimotor learning and autonomous generation of body representations, it is still not clear how such low-level representations can be scaled up to more complex motor skills and how they can enable the development of cognitive capabilities. Recent findings from behavioural and brain studies suggests that processes of mental simulations of action-perception loops are likely to be executed in our brain and are dependent on internal motor representations. The capability to simulate sensorimotor experience might represent a key mechanism behind the implementation of further cognitive skills, such as self-detection, self-other distinction and imitation. Empirical investigation on the functioning of similar processes in the brain and on their implementation in artificial agents is fragmented. This e-book comprises a collection of manuscripts published by Frontiers in Robotics and Artificial Intelligence, under the section Humanoid Robotics, on the research topic re-enactment of sensorimotor experience for cognition in artificial agents. This compendium aims at condensing the latest theoretical, review and experimental studies that address new paradigms for learning and integrating multimodal sensorimotor information in artificial agents, re-use of the sensorimotor experience for cognitive development and further construction of more complex strategies and behaviours using these concepts. The authors would like to thank M.A. Dylan Andrade for his art work for the cover.