The measurement of meaning

An Introduction to MultiAgent Systems.

The article reviews the book "The Age of Empathy: Nature's Lessons for a Kinder Society," by Frans de Waal.

The age of empathy: nature's lessons for a kinder society.

Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokemon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have bought us various degrees of digital transformation. The term `metaverse' has been coined to further facilitate the digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalysed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital `big bang' of our cyberspace is not far away. This survey paper presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems, and illustrates the possibility of the digital `big bang'. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously - Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, IoT and Robotics, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors -- Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for the development of the metaverse.

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda

Despite major advances within the affective computing research field, modelling, analysing, interpreting and responding to naturalistic human affective behaviour still remains as a challenge for automated systems as emotions are complex constructs with fuzzy boundaries and with substantial individual variations in expression and experience. Thus, a small number of discrete categories (e.g., happiness and sadness) may not reflect the subtlety and complexity of the affective states conveyed by such rich sources of information. Therefore, affective and behavioural computing researchers have recently invested increased effort in exploring how to best model, analyse, interpret and respond to the subtlety, complexity and continuity (represented along a continuum e.g., from −1 to +1) of affective behaviour in terms of latent dimensions (e.g., arousal, power and valence) and appraisals. Accordingly, this paper aims to present the current state of the art and the new challenges in automatic, dimensional and continuous analysis and synthesis of human emotional behaviour in an interdisciplinary perspective.

/pdf/emotion-representation-analysis-and-synthesis-in-continuous-1g1hi6hh7i.pdf

Emotion representation, analysis and synthesis in continuous space: A survey

This article surveys the area of computational empathy, analysing different ways by which artificial agents can simulate and trigger empathy in their interactions with humans. Empathic agents can be seen as agents that have the capacity to place themselves into the position of a user’s or another agent’s emotional situation and respond appropriately. We also survey artificial agents that, by their design and behaviour, can lead users to respond emotionally as if they were experiencing the agent’s situation. In the course of this survey, we present the research conducted to date on empathic agents in light of the principles and mechanisms of empathy found in humans. We end by discussing some of the main challenges that this exciting area will be facing in the future.

Empathy in Virtual Agents and Robots: A Survey

Expressing and recognizing affective states with respect to facial expressions is an important aspect in perceiving virtual humans as more natural and believable. Based on the results of an empirical study a system for simulating emotional facial expressions for a virtual human has been evolved. This system consists of two parts: (1) a control architecture for simulating emotional facial expressions with respect to Pleasure, Arousal, and Dominance (PAD) values, (2) an expressive output component for animating the virtual human's facial muscle actions called Action Units (AUs), modeled following the Facial Action Coding System (FACS). A large face repertoire of about 6000 faces arranged in PAD-space with respect to two dominance values (dominant vs. submissive) is obtained as a result of the empirical study. Using the face repertoire an approach towards realizing facial mimicry for a virtual human based on backward mapping AUs displaying an emotional facial expression on PAD-values is outlined. A preliminary evaluation of this first approach is realized with AUs corresponding to the basic emotions Happy and Angry.

/pdf/pleasure-arousal-dominance-driven-facial-expression-q82sswag8c.pdf

Pleasure-arousal-dominance driven facial expression simulation

Allowing virtual humans to align to others’ perceived emotions is believed to enhance their cooperative and communicative social skills. In our work, emotional alignment is realized by endowing a virtual human with the ability to empathize. Recent research shows that humans empathize with each other to different degrees depending on several factors including, among others, their mood, their personality, and their social relationships. Although providing virtual humans with features like affect, personality, and the ability to build social relationships, little attention has been devoted to the role of such features as factors modulating their empathic behavior. Supported by psychological models of empathy, we propose an approach to model empathy for the virtual human EMMA—an Empathic MultiModal Agent—consisting of three processing steps: First, the Empathy Mechanism by which an empathic emotion is produced. Second, the Empathy Modulation by which the empathic emotion is modulated. Third, the Expression of Empathy by which EMMA’s multiple modalities are triggered through the modulated empathic emotion. The proposed model of empathy is illustrated in a conversational agent scenario involving the virtual humans MAX and EMMA.

/pdf/empathy-based-emotional-alignment-for-a-virtual-human-a-3bwccbs63d.pdf

Empathy-Based Emotional Alignment for a Virtual Human: A Three-Step Approach

Empathy can be defined as the ability to perceive and understand others' emotional states. Neuropsychological evidence has shown that humans empathize with each other to different degrees depending on factors such as their mood, personality, and social relationships. Although artificial agents have been endowed with features such as affect, personality, and the ability to build social relationships, little attention has been devoted to the role of such features as factors that can modulate their empathic behavior. In this paper, we present and discuss the results of an empirical evaluation of a computational model of empathy which allows a virtual human to exhibit different degrees of empathy. Our model is supported by psychological models of empathy and is applied and evaluated in the context of a conversational agent scenario.

A Computational Model of Empathy: Empirical Evaluation

Addressing user’s emotions in human-computer interaction significantly enhances the believability and lifelikeness of virtual humans Emotion recognition and interpretation is realized in our approach by integrating empathy as a designated process within the agent’s cognitive architecture In this paper we describe this empathy process which comprises of two interconnected components: a belief-desire-intention (BDI) based cognitive component and an affective component based on the emotion simulation system of the virtual human Max The application and a preliminary evaluation of this empathy system are reported on in the context of a 3D competitive card game scenario

/pdf/simulating-empathy-for-the-virtual-human-max-2sz2smytwb.pdf

Hana Boukricha

Papers

Empathy in Virtual Agents and Robots: A Survey

Pleasure-arousal-dominance driven facial expression simulation

Empathy-Based Emotional Alignment for a Virtual Human: A Three-Step Approach

A Computational Model of Empathy: Empirical Evaluation

Simulating empathy for the virtual human Max