Memory-Centred Cognitive Architectures for Robots Interacting Socially with Humans

The Memory-Centred Cognition perspective places an active association substrate at the heart of cognition, rather than as a passive adjunct. Consequently, it places prediction and priming on the basis of prior experience to be inherent and fundamental aspects of processing. Social interaction is taken here to minimally require contingent and co-adaptive behaviours from the interacting parties. In this contribution, I seek to show how the memory-centred cognition approach to cognitive architectures can provide an means of addressing these functions. A number of example implementations are briefly reviewed, particularly focusing on multi-modal alignment as a function of experience-based priming. While there is further refinement required to the theory, and implementations based thereon, this approach provides an interesting alternative perspective on the foundations of cognitive architectures to support robots engage in social interactions with humans

A future of living machines? International trends and prospects in biomimetic and biohybrid systems

Research in the fields of biomimetic and biohybrid systems is developing at an accelerating rate. Biomimetics can be understood as the development of new technologies using principles abstracted from the study of biological systems, however, biomimetics can also be viewed from an alternate perspective as an important methodology for improving our understanding of the world we live in and of ourselves as biological organisms. A biohybrid entity comprises at least one artificial (engineered) component combined with a biological one. With technologies such as microscale mobile computing, prosthetics and implants, humankind is moving towards a more biohybrid future in which biomimetics helps us to engineer biocompatible technologies. This paper reviews recent progress in the development of biomimetic and biohybrid systems focusing particularly on technologies that emulate living organisms—living machines. Based on our recent bibliographic analysis [1] we examine how biomimetics is already creating life-like robots and identify some key unresolved challenges that constitute bottlenecks for the field. Drawing on our recent research in biomimetic mammalian robots, including humanoids, we review the future prospects for such machines and consider some of their likely impacts on society, including the existential risk of creating artifacts with significant autonomy that could come to match or exceed humankind in intelligence. We conclude that living machines are more likely to be a benefit than a threat but that we should also ensure that progress in biomimetics and biohybrid systems is made with broad societal consent. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

Autonomous decision-making for socially interactive robots

Mención Internacional en el título de doctorThe aim of this thesis is to present a novel decision-making system based on bio-inspired concepts to decide the actions to make during the interaction between humans and robots. We use concepts from nature to make the robot may behave analogously to a living being for a better acceptance by people. The system is applied to autonomous Socially Interactive Robots that works in environments with users. These objectives are motivated by the need of having robots collaborating, entertaining or helping in educational tasks for real situations with children or elder people where the robot has to behave socially. Moreover, the decision-making system can be integrated into this kind of robots in order to learn how to act depending on the user profile the robot is interacting with. The decision-making system proposed in this thesis is a solution to all these issues in addition to a complement for interactive learning in HRI. We also show real applications of the system proposed applying it in an educational scenario, a situation where the robot can learn and interact with different kinds of people. The last goal of this thesis is to develop a robotic architecture that is able to learn how to behave in different contexts where humans and robots coexist. For that purpose, we design a modular and portable robotic architecture that is included in several robots. Including well-known software engineering techniques together with innovative agile software development procedures that produces an easily extensible architecture.El objetivo de esta tesis es presentar un novedoso sistema de toma de decisiones basado en conceptos bioinspirados para decidir las acciones a realizar durante la interacción entre personas y robots. Usamos conceptos de la naturaleza para hacer que el robot pueda comportarse análogamente a un ser vivo para una mejor aceptación por las personas. El sistema está desarrollado para que se pueda aplicar a los llamados Robots Socialmente Interactivos que están destinados a entornos con usuarios. Estos objetivos están motivados por la necesidad de tener robots en tareas de colaboración, entretenimiento o en educación en situaciones reales con niños o personas mayores en las cuales el robot debe comportarse siguiendo las normas sociales. Además, el sistema de toma de decisiones es integrado en estos tipos de robots con el fin de que pueda aprender a actuar dependiendo del perfil de usuario con el que el robot está interactuando. El sistema de toma de decisiones que proponemos en esta tesis es una solución a todos estos desafíos además de un complemento para el aprendizaje interactivo en la interacción humano-robot. También mostramos aplicaciones reales del sistema propuesto aplicándolo en un escenario educativo, una situación en la que el robot puede aprender e interaccionar con diferentes tipos de personas. El último objetivo de esta tesis es desarrollar un arquitectura robótica que sea capaz de aprender a comportarse en diferentes contextos donde las personas y los robots coexistan. Con ese propósito, diseñamos una arquitectura robótica modular y portable que está incluida en varios robots. Incluyendo técnicas bien conocidas de ingeniería del software junto con procedimientos innovadores de desarrollo de sofware ágil que producen una arquitectura fácilmente extensible.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Fabio Bonsignorio.- Secretario: María Dolores Blanco Rojas.- Vocal: Martin Stoele

From social brains to social robots: applying neurocognitive insights to human-robot interaction

Amidst the fourth industrial revolution, social robots are resolutely moving from fiction to reality. With sophisticated artificial agents becoming ever more ubiquitous in daily life, researchers across different fields are grappling with the questions concerning how humans perceive and interact with these agents and the extent to which the human brain incorporates intelligent machines into our social milieu. This theme issue surveys and discusses the latest findings, current challenges and future directions in neuroscience- and psychology-inspired human–robot interaction (HRI). Critical questions are explored from a transdisciplinary perspective centred around four core topics in HRI: technical solutions for HRI, development and learning for HRI, robots as a tool to study social cognition, and moral and ethical implications of HRI. Integrating findings from diverse but complementary research fields, including social and cognitive neurosciences, psychology, artificial intelligence and robotics, the contributions showcase ways in which research from disciplines spanning biological sciences, social sciences and technology deepen our understanding of the potential and limits of robotic agents in human social life

How to Do Things Without Words: Infants, utterance-activity and distributed cognition

Clark and Chalmers (1998) defend the hypothesis of an ‘Extended Mind’, maintaining that beliefs and other paradigmatic mental states can be implemented outside the central nervous system or body. Aspects of the problem of ‘language acquisition’ are considered in the light of the extended mind hypothesis. Rather than ‘language’ as typically understood, the object of study is something called ‘utterance-activity’, a term of art intended to refer to the full range of kinetic and prosodic features of the on-line behaviour of interacting humans. It is argued that utterance activity is plausibly regarded as jointly controlled by the embodied activity of interacting people, and that it contributes to the control of their behaviour. By means of specific examples it is suggested that this complex joint control facilitates easier learning of at least some features of language. This in turn suggests a striking form of the extended mind, in which infants’ cognitive powers are augmented by those of the people with whom they interact

Workshop: Cognitive Architectures for Social Human-Robot Interaction

Social HRI requires robots able to use appropriate, adaptive and contingent behaviours to form and maintain en- gaging social interactions with people. Cognitive Architectures emphasise a generality of mechanism and application, making them an ideal basis for such technical developments. Following the successful first workshop on Cognitive Architectures for HRI at the 2014 HRI conference, this second edition of the workshop focusses specifically on applications to social interaction. The full-day workshop is centred on participant contributions, and structured around a set of questions to provide a common basis of comparison between different assumptions, approaches, mechanisms, and architectures. These contributions will be used to support extensive and structured discussions, with the aim of facilitating the development and application of cognitive architectures to social HRI systems. By attending, we envisage that participants will gain insight into how the consideration of cognitive architectures complements the development of au- tonomous social robots

A Systematic Review of Adaptivity in Human-Robot Interaction

As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past interactions. Therefore, we believe it is significant to report a review of the past research on the use of adaptive robots that have been utilised in various social environments. In this paper, we present a systematic review on the reported adaptive interactions across a number of domain areas during Human-Robot Interaction and also give future directions that can guide the design of future adaptive social robots. We conjecture that this will help towards achieving long-term applicability of robots in various social domains