This is the second of a three-volume set that constitutes the refereed proceedings of the 4th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2007, held in Beijing, China. Devoted to ambient interaction, it covers intelligent ambients, access to the physical environment, mobility and transportation, virtual and augmented environments, as well as interaction techniques and devices.

An exploration of embodied intelligence and its implications points toward a theory of intelligence in general; with case studies of intelligent systems in ubiquitous computing, business and management, human memory, and robotics. How could the body influence our thinking when it seems obvious that the brain controls the body? In How the Body Shapes the Way We Think, Rolf Pfeifer and Josh Bongard demonstrate that thought is not independent of the body but is tightly constrained, and at the same time enabled, by it. They argue that the kinds of thoughts we are capable of have their foundation in our embodiment—in our morphology and the material properties of our bodies. This crucial notion of embodiment underlies fundamental changes in the field of artificial intelligence over the past two decades, and Pfeifer and Bongard use the basic methodology of artificial intelligence—"understanding by building"—to describe their insights. If we understand how to design and build intelligent systems, they reason, we will better understand intelligence in general. In accessible, nontechnical language, and using many examples, they introduce the basic concepts by building on recent developments in robotics, biology, neuroscience, and psychology to outline a possible theory of intelligence. They illustrate applications of such a theory in ubiquitous computing, business and management, and the psychology of human memory. Embodied intelligence, as described by Pfeifer and Bongard, has important implications for our understanding of both natural and artificial intelligence.

Humanoid Robotics provides a comprehensive compilation of developments in the conceptualization, design and development of humanoid robots and related technologies. Human beings have built the environment they occupy (living spaces, instruments and vehicles) to suit two-legged systems. Building systems, especially in robotics, that are compatible with the well-established, human-based surroundings and which could naturally interact with humans is an ultimate goal for all researches and engineers. Humanoid Robots are systems (i.e. robots) which mimic human behavior. Humanoids provide a platform to study the construction of systems that behave and interact like humans. A broad range of applications ranging from daily housework to complex medical surgery, deep ocean exploration, and other potentially dangerous tasks are possible using humanoids. In addition, the study of humanoid robotics provides a platform to understand the mechanisms and offers a physical visual of how humans interact, think, and react with the surroundings and how such behaviors could be reassembled and reconstructed. Currently, the most challenging issue with bipedal humanoids is to make them balance on two legs, The purportedly simple act of finding the best balance that enables easy walking, jumping and running requires some of the most sophisticated development of robotic systems- those that will ultimately mimic fully the diversity and dexterity of human beings. Other typical human-like interactions such as complex thought and conversations on the other hand, also pose barriers for the development of humanoids because we are yet to understand fully the way in which we humans interact with our environment and consequently to replicate this in humanoids.

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.