3,409 research outputs found

    Affect and believability in game characters:a review of the use of affective computing in games

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    Virtual agents are important in many digital environments. Designing a character that highly engages users in terms of interaction is an intricate task constrained by many requirements. One aspect that has gained more attention recently is the effective dimension of the agent. Several studies have addressed the possibility of developing an affect-aware system for a better user experience. Particularly in games, including emotional and social features in NPCs adds depth to the characters, enriches interaction possibilities, and combined with the basic level of competence, creates a more appealing game. Design requirements for emotionally intelligent NPCs differ from general autonomous agents with the main goal being a stronger player-agent relationship as opposed to problem solving and goal assessment. Nevertheless, deploying an affective module into NPCs adds to the complexity of the architecture and constraints. In addition, using such composite NPC in games seems beyond current technology, despite some brave attempts. However, a MARPO-type modular architecture would seem a useful starting point for adding emotions

    Robot Betrayal: a guide to the ethics of robotic deception

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    If a robot sends a deceptive signal to a human user, is this always and everywhere an unethical act, or might it sometimes be ethically desirable? Building upon previous work in robot ethics, this article tries to clarify and refine our understanding of the ethics of robotic deception. It does so by making three arguments. First, it argues that we need to distinguish between three main forms of robotic deception (external state deception; superficial state deception; and hidden state deception) in order to think clearly about its ethics. Second, it argues that the second type of deception – superficial state deception – is not best thought of as a form of deception, even though it is frequently criticised as such. And third, it argues that the third type of deception is best understood as a form of betrayal because doing so captures the unique ethical harm to which it gives rise, and justifies special ethical protections against its use

    Assistive robotics: research challenges and ethics education initiatives

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    Assistive robotics is a fast growing field aimed at helping healthcarers in hospitals, rehabilitation centers and nursery homes, as well as empowering people with reduced mobility at home, so that they can autonomously fulfill their daily living activities. The need to function in dynamic human-centered environments poses new research challenges: robotic assistants need to have friendly interfaces, be highly adaptable and customizable, very compliant and intrinsically safe to people, as well as able to handle deformable materials. Besides technical challenges, assistive robotics raises also ethical defies, which have led to the emergence of a new discipline: Roboethics. Several institutions are developing regulations and standards, and many ethics education initiatives include contents on human-robot interaction and human dignity in assistive situations. In this paper, the state of the art in assistive robotics is briefly reviewed, and educational materials from a university course on Ethics in Social Robotics and AI focusing on the assistive context are presented.Peer ReviewedPostprint (author's final draft

    A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

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    In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

    Artificial Companions with Personality and Social Role

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    Subtitle: "Expectations from Users on the Design of Groups of Companions"International audienceRobots and virtual characters are becoming increasingly used in our everyday life. Yet, they are still far from being able to maintain long-term social relationships with users. It also remains unclear what future users will expect from these so-called "artificial companions" in terms of social roles and personality. These questions are of importance because users will be surrounded with multiple artificial companions. These issues of social roles and personality among a group of companions are sledom tackled in user studies. In this paper, we describe a study in which 94 participants reported that social roles and personalities they would expect from groups of companions. We explain how the resulsts give insights for the design of future groups of companions endowed with social intelligence

    If I Can\u27t Predict My Future, Why Can AI? Exploring Human Interaction with Predictive Analytics

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    This research study seeks to understand how AI-based chatbots can potentially be leveraged as a tool in a PSYOP. This study is methodologically driven as it employs validated scales concerning suggestibility and human-computer interaction to assess how participants interact with a specific AI chatbot, Replika. Recent studies demonstrate the capability of GPT-based analytics to influence user’s moral judgements, and this paper is interested in exploring why. Results will help draw conclusions regarding human interaction with predictive analytics (in this case a free GPT-based chatbot, Replika) to understand if suggestibility (how easily influenced someone generally is) impacts the overall usability of AI chatbots. This project will help assess how much of a concern predictive AI chatbots should be considered as virtual AI influencers and other bot-based propaganda modalities emerge in the contemporary media environment. This study uses the CASA paradigm, medium theory, and Boyd’s theory of conflict to explore how factors that often drive human computer interaction— like anthropomorphic autonomy and suspension of disbelief— potentially relate to suggestibility or chatbot usability. Overall, this study is interested in specifically exploring if suggestion can predict usability in AI chatbots

    The challenge of complexity for cognitive systems

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    Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research

    An Evolving Apparatus

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

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    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
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