Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

Artificial Intelligence: Robots, Avatars, and the Demise of the Human Mediator

Published in cooperation with the American Bar Association Section of Dispute Resolutio

Artificial Intelligence: Robots, Avatars, and the Demise of the Human Mediator

Published in cooperation with the American Bar Association Section of Dispute Resolutio

Artificial Intelligence: Robots, Avatars and the Demise of the Human Mediator

As technology has advanced, many have wondered whether (or simply when) artificial intelligent devices will replace the humans who perform complex, interactive, interpersonal tasks such as dispute resolution. Has science now progressed to the point that artificial intelligence devices can replace human mediators, arbitrators, dispute resolvers and problem solvers? Can humanoid robots, attractive avatars and other relational agents create the requisite level of trust and elicit the truthful, perhaps intimate or painful, disclosures often necessary to resolve a dispute or solve a problem? This article will explore these questions. Regardless of whether the reader is convinced that the demise of the human mediator or arbitrator is imminent, one cannot deny that artificial intelligence now has the capability to assume many of the responsibilities currently being performed by alternative dispute resolution (ADR) practitioners. It is fascinating (and perhaps unsettling) to realize the complexity and seriousness of tasks currently delegated to avatars and robots. This article will review some of those delegations and suggest how the artificial intelligence developed to complete those assignments may be relevant to dispute resolution and problem solving. “Relational Agents,” which can have a physical presence such as a robot, be embodied in an avatar, or have no detectable form whatsoever and exist only as software, are able to create long term socio-economic relationships with users built on trust, rapport and therapeutic goals. Relational agents are interacting with humans in circumstances that have significant consequences in the physical world. These interactions provide insights as to how robots and avatars can participate productively in dispute resolution processes. Can human mediators and arbitrators be replaced by robots and avatars that not only physically resemble humans, but also act, think, and reason like humans? And to raise a particularly interesting question, can robots, avatars and other relational agents look, move, act, think, and reason even “better” than humans

A Novel Reinforcement-Based Paradigm for Children to Teach the Humanoid Kaspar Robot

© The Author(s) 2019. This is the final published version of an article published in Psychological Research, licensed under a Creative Commons Attri-bution 4.0 International License. Available online at: https://doi.org/10.1007/s12369-019-00607-xThis paper presents a contribution to the active field of robotics research with the aim of supporting the development of social and collaborative skills of children with Autism Spectrum Disorders (ASD). We present a novel experiment where the classical roles are reversed: in this scenario the children are the teachers providing positive or negative reinforcement to the Kaspar robot in order for the robot to learn arbitrary associations between different toy names and the locations where they are positioned. The objective of this work is to develop games which help children with ASD develop collaborative skills and also provide them tangible example to understand that sometimes learning requires several repetitions. To facilitate this game we developed a reinforcement learning algorithm enabling Kaspar to verbally convey its level of uncertainty during the learning process, so as to better inform the children interacting with Kaspar the reasons behind the successes and failures made by the robot. Overall, 30 Typically Developing (TD) children aged between 7 and 8 (19 girls, 11 boys) and 6 children with ASD performed 22 sessions (16 for TD; 6 for ASD) of the experiment in groups, and managed to teach Kaspar all associations in 2 to 7 trials. During the course of study Kaspar only made rare unexpected associations (2 perseverative errors and 1 win-shift, within a total of 272 trials), primarily due to exploratory choices, and eventually reached minimal uncertainty. Thus the robot's behavior was clear and consistent for the children, who all expressed enthusiasm in the experiment.Peer reviewe

Guidance in storytelling tables supports emotional development in kindergartners

Promoting the social-emotional development of kindergartners is of special relevance as will lay the foundations for emotion regulation in later childhood and adulthood stages. Considering that tangible storytelling tables are already used for language and literacy skills in kindergarten, we addressed the problem of designing a storytelling intervention aimed at social-emotional development suitable in such a context by using an emotional laden story as content and embedding a guidance method that can be implemented with either a human or robot guide to enhance the learning setting. The study considered two guided storytelling activities (one traditional guided by the teacher, and one in which guidance was provided by a robot) and a control condition without additional guidance. The three conditions were compared in terms of kindergartners’ enactment process, an emotion recognition test and a story recall test. The results show that the guidance method properly supported emotion naming, children involvement and goal completion during the storytelling activity whereas the intervention supported the learning gain on emotion recognition. The study revealed that both robot and human guidance did not differ significantly in the performance tests but did outperform the control. In view of the results, this research is helpful for researchers and teachers to create in an informed way a range of environments in the kindergarten class based on storytelling tables, either with or without guidance, and with or without robot support. Future work may further investigate how specific interaction issues concerning robot embodiment (e.g., voice and behavioral cues to direct children’s attention) might enhance or not the children’s performanceOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work has partially been funded by the Spanish Ministry of Science, Innovation and Universities under Juan de la Cierva programme (IJC2018–037522-I). The writing of this work has received financial support from the Consellería de Educación, Universidade e Formación Profesional (accreditation 2019–2022 ED431G-2019/04, reference ED431C2022/19) and the European Regional Development Fund (ERDF)S

Social Robots in Collaborative Learning: Consequences of the Design on Students' Perception

International audienc

BlueSky: Combining Task Planning and Activity-Centric Access Control for Assistive Humanoid Robots

In the not too distant future, assistive humanoid robots will provide versatile assistance for coping with everyday life. In their interactions with humans, not only safety, but also security and privacy issues need to be considered. In this Blue Sky paper, we therefore argue that it is time to bring task planning and execution as a well-established field of robotics with access and usage control in the field of security and privacy closer together. In particular, the recently proposed activity-based view on access and usage control provides a promising approach to bridge the gap between these two perspectives. We argue that humanoid robots provide for specific challenges due to their task-universality and their use in both, private and public spaces. Furthermore, they are socially connected to various parties and require policy creation at runtime due to learning. We contribute first attempts on the architecture and enforcement layer as well as on joint modeling, and discuss challenges and a research roadmap also for the policy and objectives layer. We conclude that the underlying combination of decentralized systems\u27 and smart environments\u27 research aspects provides for a rich source of challenges that need to be addressed on the road to deployment

Enriching conflict resolution environments with the provision of context information

It is a common affair to settle disputes out of courts nowadays, through negotiation, mediation or any other mean. This has also been implemented over telecommunication means under the so-called Online Dispute Resolution methods. However, this new technology-supported approach is impersonal and cold, leaving aside important issues such as the disputants’ body language, stress level or emotional response while being based on forms, e-mails or chat rooms. To overcome this shortcoming in this paper it is proposed the creation of intelligent environments for conflict resolution that can complement the existing tools with important knowledge about the context of interaction. This will allow decisionmakers to take better framed decisions based not only on figures but also on important contextual information, similarly to what happens when parties communicate in the physical presence of each other.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012) and PEst-OE/ EEI/UI0752/2011. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009).info:eu-repo/semantics/publishedVersio