Design and Experimental Evaluation of a Context-aware Social Gaze Control System for a Humanlike Robot

Nowadays, social robots are increasingly being developed for a variety of human-centered scenarios in which they interact with people. For this reason, they should possess the ability to perceive and interpret human non-verbal/verbal communicative cues, in a humanlike way. In addition, they should be able to autonomously identify the most important interactional target at the proper time by exploring the perceptual information, and exhibit a believable behavior accordingly. Employing a social robot with such capabilities has several positive outcomes for human society. This thesis presents a multilayer context-aware gaze control system that has been implemented as a part of a humanlike social robot. Using this system the robot is able to mimic the human perception, attention, and gaze behavior in a dynamic multiparty social interaction. The system enables the robot to direct appropriately its gaze at the right time to the environmental targets and humans who are interacting with each other and with the robot. For this reason, the attention mechanism of the gaze control system is based on features that have been proven to guide human attention: the verbal and non-verbal cues, proxemics, the effective field of view, the habituation effect, and the low-level visual features. The gaze control system uses skeleton tracking and speech recognition,facial expression recognition, and salience detection to implement the same features. As part of a pilot evaluation, the gaze behavior of 11 participants was collected with a professional eye-tracking device, while they were watching a video of two-person interactions. Analyzing the average gaze behavior of participants, the importance of human-relevant features in human attention triggering were determined. Based on this finding, the parameters of the gaze control system were tuned in order to imitate the human behavior in selecting features of environment. The comparison between the human gaze behavior and the gaze behavior of the developed system running on the same videos shows that the proposed approach is promising as it replicated human gaze behavior 89% of the time

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

Drama, a connectionist model for robot learning: experiments on grounding communication through imitation in autonomous robots

The present dissertation addresses problems related to robot learning from demonstra¬ tion. It presents the building of a connectionist architecture, which provides the robot with the necessary cognitive and behavioural mechanisms for learning a synthetic lan¬ guage taught by an external teacher agent. This thesis considers three main issues: 1) learning of spatio-temporal invariance in a dynamic noisy environment, 2) symbol grounding of a robot's actions and perceptions, 3) development of a common symbolic representation of the world by heterogeneous agents.We build our approach on the assumption that grounding of symbolic communication creates constraints not only on the cognitive capabilities of the agent but also and especially on its behavioural capacities. Behavioural skills, such as imitation, which allow the agent to co-ordinate its actionn to that of the teacher agent, are required aside to general cognitive abilities of associativity, in order to constrain the agent's attention to making relevant perceptions, onto which it grounds the teacher agent's symbolic expression. In addition, the agent should be provided with the cognitive capacity for extracting spatial and temporal invariance in the continuous flow of its perceptions. Based on this requirement, we develop a connectionist architecture for learning time series. The model is a Dynamical Recurrent Associative Memory Architecture, called DRAMA. It is a fully connected recurrent neural network using Hebbian update rules. Learning is dynamic and unsupervised. The performance of the architecture is analysed theoretically, through numerical simulations and through physical and simulated robotic experiments. Training of the network is computationally fast and inexpensive, which allows its implementation for real time computation and on-line learning in a inexpensive hardware system. Robotic experiments are carried out with different learning tasks involving recognition of spatial and temporal invariance, namely landmark recognition and prediction of perception-action sequence in maze travelling.The architecture is applied to experiments on robot learning by imitation. A learner robot is taught by a teacher agent, a human instructor and another robot, a vocabulary to describe its perceptions and actions. The experiments are based on an imitative strategy, whereby the learner robot reproduces the teacher's actions. While imitating the teacher's movements, the learner robot makes similar proprio and exteroceptions to those of the teacher. The learner robot grounds the teacher's words onto the set of common perceptions they share. We carry out experiments in simulated and physical environments, using different robotic set-ups, increasing gradually the complexity of the task. In a first set of experiments, we study transmission of a vocabulary to designate actions and perception of a robot. Further, we carry out simulation studies, in which we investigate transmission and use of the vocabulary among a group of robotic agents. In a third set of experiments, we investigate learning sequences of the robot's perceptions, while wandering in a physically constrained environment. Finally, we present the implementation of DRAMA in Robota, a doll-like robot, which can imitate the arms and head movements of a human instructor. Through this imitative game, Robota is taught to perform and label dance patterns. Further, Robota is taught a basic language, including a lexicon and syntactical rules for the combination of words of the lexicon, to describe its actions and perception of touch onto its body

The Nexus between Artificial Intelligence and Economics

This book is organized as follows. Section 2 introduces the notion of the Singularity, a stage in development in which technological progress and economic growth increase at a near-infinite rate. Section 3 describes what artificial intelligence is and how it has been applied. Section 4 considers artificial happiness and the likelihood that artificial intelligence might increase human happiness. Section 5 discusses some prominent related concepts and issues. Section 6 describes the use of artificial agents in economic modeling, and section 7 considers some ways in which economic analysis can offer some hints about what the advent of artificial intelligence might bring. Chapter 8 presents some thoughts about the current state of AI and its future prospects.

Persuasiveness of social robot ‘Nao’ based on gaze and proximity

Social Robots have widely infiltrated the retail and public space. Mainly, social robots are being utilized across a wide range of scenarios to influence decision making, disseminate information, and act as a signage mechanism, under the umbrella of Persuasive Robots or Persuasive Technology. While there have been several studies in the afore-mentioned area, the effect of non-verbal behaviour on persuasive abilities is generally unexplored. Therefore, in this research, we report whether two key non-verbal attributes, namely proximity and gaze, can elicit persuasively, compliance, and specific personality appeals. For this, we conducted a 2 (eye gaze) x 2 (proximity) between-subjects experiment where participants viewed a video-based scenario of the Nao robot. Our initial results did not reveal any significant results based on the non-verbal attributes. However, perceived compliance and persuasion were significantly correlated with knowledge, responsiveness, and trustworthiness. In conclusion, we discuss how the design of a robot could make it more convincing as extensive marketing and brand promotion companies could use robots to enhance their advertisement operations

Artificial intelligence and robots in services : theory and management of (future) humanrobot service interactions

During the past decade, service robots have increasingly been deployed in a wide variety of services, where they co-produce service outcomes with and for the benefit of internal or external customers within humanrobot service interactions (HRSI). Although the introduction of different service robot types into the marketplace promises efficiency gains, it changes premises of service encounter theory and practice fundamentally. Moreover, introducing service robots without considering external or internal customers needs can lead to negative service outcomes. This thesis aims to generate knowledge on how the introduction of different service robot types (i.e., embodied and digital service robots) in internal and external service encounters changes fundamental premises of service encounter theory and impacts HRSI outcomes. In doing so, it leverages different scientific methods and focuses on external service encounters with digital and embodied service robots, as well as internal service encounters with digital service robots. Chapter 2 aims to advance service encounter theory in the context of HRSI in external service encounters by conceptually developing a service encounter theory evaluation scheme to assess a theorys fit to explain HRSI-related phenomena. The scheme includes individual and contextual factors that bound theoretical premises and, hence, supports scholars in assessing standing service encounter theories. The chapter also puts forth an exemplary assessment of role theory and provides detailed avenues for future research. Chapter 3 aims to synthesize the great wealth of knowledge on HRSI related to external service encounters with embodied service robots. By conducting a comprehensive systematic literature review, the chapter identifies 199 empirical research articles across scientific fields that can inform service research on how to successfully introduce service robots into the organizational frontline. To organize the plethora of research findings, this chapter develops a new structuring framework (D3: design, delegate, deploy). It utilizes this framework to provide a comprehensive overview of the empirical HRSI literature, delineates practical implications, and identifies gaps in literature to identify promising future research avenues. Chapter 4 also addresses HRSI in external service encounters but focuses specifically on the transformative potential of embodied service robots to enhance vulnerable consumers (i.e., children and older adults) well-being in social isolation. To identify how different robots can enhance well-being, this chapter follows a conceptual approach and integrates findings from service research, social robotics, social psychology, and medicine. The chapter develops a typology of robotic transformative service (i.e., entertainer, social enabler, mentor, and friend) as a function of consumers state of social isolation, well-being focus, and robot capabilities and a future research agenda for robotic transformative service research (RTSR). This work guides service consumers and providers, as well as robot developers, in identifying and developing the most appropriate robot type for advancing the well-being of vulnerable consumers in social isolation. Finally, Chapter 5 focuses on HRSI research in the context of interactions with digital service robots in internal service encounters. Based on a comprehensive literature review paired with a qualitative study, it conceptionally develops a new concept of a collaborative, digital service robot: a collaborative intelligence system (i.e., CI system) that co-produces service with employees. Drawing from service encounter needs theory, the chapter also empirically tests the effect of CI systems on employee need fulfillment (i.e., need for control, cognition, self-efficacy, and justice) and, in turn, on responsibility taking in two scenario-based experiments. The results uncover divergent mechanisms of how the fulfillment of service encounter needs drives the effect of CI systems on outcome responsibility for different employee groups. Service scholars and managers benefit from a blueprint for designing collaborative digital service robots and an understanding of their effects on employee outcomes in service co-production. In summary, this thesis contributes to literature by providing new insights into different types of HRSI by consolidating HRSI knowledge, developing and advancing HRSI concepts and theory, and empirically investigating HRSI-related phenomena. The new insights put forth in this thesis are discussed and implications for service theory and practice are delineated.Serviceroboter werden zunehmend für Dienstleistungen eingesetzt, wobei sie mit und zum Nutzen von internen oder externen Kunden im Rahmen von Mensch-Roboter-Service-Interaktionen (MRSI) Serviceergebnisse co-produzieren. Die Einführung verschiedener Arten von Servicerobotern (d. h. verkörperte und digitale) verspricht Effizienzgewinne, verändert jedoch grundlegende Prämissen der Theorie und Praxis von Dienstleistungsinteraktionen. Darüber hinaus kann die Einführung von Servicerobotern ohne die Berücksichtigung von Kundenbedürfnissen zu negativen Serviceergebnissen führen. Ziel dieser Dissertation ist es, Wissen darüber zu generieren, wie die Einführung verschiedener Robotertypen in internen und externen Dienstleistungsinteraktionen grundlegende theoretische Prämissen von Dienstleistungsinteraktionen verändert und sich auf die Ergebnisse von MRSI auswirkt. Um dieses Ziel zu erreichen werden unter Einsatz verschiedener wissenschaftlicher Methoden drei verschiedene Arten von MRSI untersucht. Kapitel 2 zielt darauf ab, die Theorie der Dienstleistungsinteraktion im Kontext von MRSI in externen Dienstleistungsinteraktionen weiterzuentwickeln und konzeptioniert ein Bewertungsschema für bestehende Theorien der Dienstleistungsbegegnung. Das Schema umfasst individuelle und kontextuelle Faktoren, die die ursprünglichen theoretischen Prämissen von Mensch-zu-Mensch Dienstleistungsinteraktionen beeinflussen und unterstützt somit Wissenschaftler bei der Bewertung von Theorien zur Verwendung im MRSI Kontext. Das Kapitel enthält eine beispielhafte Bewertung der Rollentheorie und zeigt detaillierte Wege für zukünftige Forschung auf. Kapitel 3 zielt darauf ab, die große Fülle an Wissen über MRSI im Kontext externer Dienstleistungsinteraktionen mit verkörperten Servicerobotern zu synthetisieren. Durch eine systematische, interdisziplinäre Literaturanalyse identifiziert das Kapitel 199 empirische Forschungsartikel, die Erkenntnisse liefern, wie Serviceroboter erfolgreich in den Dienstleistungsprozess eingebunden werden können. Um die Fülle an Forschungsergebnissen zu ordnen, entwickelt dieses Kapitel ein neues, strukturierendes Modell (D3 framework: design, delegate, deploy). Dieses wird im Rahmen des Kapitels genutzt, um einen umfassenden Überblick über die empirische MRSI-Forschung zu geben, praktische Implikationen abzuleiten und Forschungslücken aufzuzeigen. Kapitel 4 befasst sich ebenfalls mit MRSI in externen Dienstleistungsinteraktionen, konzentriert sich aber auf das transformative Potenzial von verkörperten Servicerobotern zur Steigerung des Wohlbefindens von sozial isolierten, vulnerablen Verbrauchern (d. h. Kinder und ältere Erwachsene). Um herauszufinden, wie verschiedene Roboter das Wohlbefinden steigern können, integriert das Kapitel Erkenntnisse aus der Dienstleistungsforschung, der sozialen Robotik, der Sozialpsychologie und der Medizin. Dabei wird eine Typologie von vier transformativen Robotern in Abhängigkeit vom Zustand der sozialen Isolation des Verbrauchers, der Art des Wohlbefindens und den Fähigkeiten des Roboters entwickelt. Weiterhin wird eine detaillierte Forschungsagenda im Kontext transformativer Dienstleistungserstellung durch Roboter erarbeitet. Diese Arbeit hilft Dienstleistungsnehmern und -anbietern sowie Roboterentwicklern bei der Identifizierung und Entwicklung des am besten geeigneten Robotertyps zur Förderung des Wohlbefindens von sozial isolierten, vulnerablen Verbrauchern. Abschließend fokussiert Kapitel 5 die MRSI-Forschung im Kontext interner Dienstleistungsinteraktionen mit digitalen Servicerobotern. Auf Basis einer Literaturanalyse gepaart mit einer qualitativen Studie wird ein neues Konzept eines kollaborativen, digitalen Serviceroboters entwickelt: ein Collaborative Intelligence System (CI System), das in Zusammenarbeit mit Mitarbeitern Dienstleistungsergebnisse co-produziert. Anhand szenariobasierter Experimente wird empirisch untersucht, ob CI Systeme psychosoziale Bedürfnisse von Mitarbeitern befriedigen können und damit die mitarbeiterseitige Übernahme von Verantwortung für gemeinsam produzierte Ergebnisse gefördert wird. Die Ergebnisse decken für verschiedene Mitarbeitergruppen unterschiedliche Mechanismen auf, wie die Erfüllung von Bedürfnissen in der Dienstleistungsinteraktionen die Wirkung von CI Systemen auf die mitarbeiterseitige Übernahme von Verantwortung beeinflusst. Dienstleistungsforscher und -manager profitieren von einer Blaupause für die Gestaltung kollaborativer Dienstleistungsroboter und einem Verständnis für deren Auswirkungen auf Mitarbeitende. Insgesamt leistet diese Dissertation einen Beitrag zur Dienstleistungsforschung, indem sie neue Erkenntnisse über verschiedene Arten von MRSI liefert, das bestehende MRSI-Wissen konsolidiert, neue MRSI-Konzepte und -Theorien entwickelt bzw. weiterentwickelt und MRSI-bezogene Phänomene empirisch untersucht. Die neuen Erkenntnisse werden diskutiert und Implikationen für die Dienstleistungstheorie und -praxis abgeleitet

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming