Embodied Robot Models for Interdisciplinary Emotion Research

Due to their complex nature, emotions cannot be properly understood from the perspective of a single discipline. In this paper, I discuss how the use of robots as models is beneficial for interdisciplinary emotion research. Addressing this issue through the lens of my own research, I focus on a critical analysis of embodied robots models of different aspects of emotion, relate them to theories in psychology and neuroscience, and provide representative examples. I discuss concrete ways in which embodied robot models can be used to carry out interdisciplinary emotion research, assessing their contributions: as hypothetical models, and as operational models of specific emotional phenomena, of general emotion principles, and of specific emotion ``dimensions''. I conclude by discussing the advantages of using embodied robot models over other models.Peer reviewe

Simple environments fail as illustrations of intelligence: A review of R. Pfeifer and C. Scheier

The field of cognitive science has always supported a variety of modes of research, often polarised into those seeking high-level explanations of intelligence and those seeking low-level, perhaps even neuro-physiological, explanations. Each of these research directions permits, at least in part, a similar methodology based around the construction of detailed computational models, which justify their explanatory claims by matching behavioural data. We are fortunate at this time to witness the culmination of several decades of work from each of these research directions, and hopefully to find within them the basic ideas behind a complete theory of human intelligence. It is in this spirit that Rolf Pfeifer and Christian Scheier have written their book Understanding Intelligence. However, their aim is manifestly not to present an overview of all prior work in this field, but instead to argue forcefully for one particular interpretation – a synthetic approach, based around the explicit construction of autonomous agents. This approach is characterised by the Embodiment Hypothesis, which is presented as a complete framework for investigating intelligence, and exemplified by a number of computational models and robots to illustrate just how the field of cognitive science might develop in the future. We first provide an overview of their book, before describing some of our reservations about its contribution towards an understanding of intelligence

On the Role of AI in the Ongoing Paradigm Shift within the Cognitive Sciences

This paper supports the view that the ongoing shift from orthodox to embodied-embedded cognitive science has been significantly influenced by the experimental results generated by AI research. Recently, there has also been a noticeable shift toward enactivism, a paradigm which radicalizes the embodied-embedded approach by placing autonomous agency and lived subjectivity at the heart of cognitive science. Some first steps toward a clarification of the relationship of AI to this further shift are outlined. It is concluded that the success of enactivism in establishing itself as a mainstream cognitive science research program will depend less on progress made in AI research and more on the development of a phenomenological pragmatics

Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”This position paper proposes that the study of embodied cognitive agents, such as humanoid robots, can advance our understanding of the cognitive development of complex sensorimotor, linguistic, and social learning skills. This in turn will benefit the design of cognitive robots capable of learning to handle and manipulate objects and tools autonomously, to cooperate and communicate with other robots and humans, and to adapt their abilities to changing internal, environmental, and social conditions. Four key areas of research challenges are discussed, specifically for the issues related to the understanding of: 1) how agents learn and represent compositional actions; 2) how agents learn and represent compositional lexica; 3) the dynamics of social interaction and learning; and 4) how compositional action and language representations are integrated to bootstrap the cognitive system. The review of specific issues and progress in these areas is then translated into a practical roadmap based on a series of milestones. These milestones provide a possible set of cognitive robotics goals and test scenarios, thus acting as a research roadmap for future work on cognitive developmental robotics.Peer reviewe