From individual characters to large crowds: augmenting the believability of open-world games through exploring social emotion in pedestrian groups

Crowds of non-player characters improve the game-play experiences of open-world video-games. Grouping is a common phenomenon of crowds and plays an important role in crowd behaviour. Recent crowd simulation research focuses on group modelling in pedestrian crowds and game-designers have argued that the design of non-player characters should capture and exploit the relationship between characters. The concepts of social groups and inter-character relationships are not new in social psychology, and on-going work addresses the social life of emotions and its behavioural consequences on individuals and groups alike. The aim of this paper is to provide an overview of current research in social psychology, and to use the findings as a source of inspiration to design a social network of non-player characters, with application to the problem of group modelling in simulated crowds in computer games

An Appraisal-Based Chain-Of-Emotion Architecture for Affective Language Model Game Agents

The development of believable, natural, and interactive digital artificial agents is a field of growing interest. Theoretical uncertainties and technical barriers present considerable challenges to the field, particularly with regards to developing agents that effectively simulate human emotions. Large language models (LLMs) might address these issues by tapping common patterns in situational appraisal. In three empirical experiments, this study tests the capabilities of LLMs to solve emotional intelligence tasks and to simulate emotions. It presents and evaluates a new chain-of-emotion architecture for emotion simulation within video games, based on psychological appraisal research. Results show that it outperforms standard LLM architectures on a range of user experience and content analysis metrics. This study therefore provides early evidence of how to construct and test affective agents based on cognitive processes represented in language models

Stereotyping human-like virtual influencers in retailing: Does warmth prevail over competence?

Building upon the Stereotype Content Model (SCM), the current research provides insights into how virtual influencers (VIs) influence consumer responses. More specifically, it investigates the associations between the VI's anthropomorphism and stereotypical judgments of the VI's warmth and competence as well as the differential and mediating roles of these stereotypes in influencing consumers' willingness to follow the VI's recommendations and purchase intentions. The results support the idea that anthropomorphizing VIs has a direct bearing on stereotyping VIs along the competence and warmth dimensions of the SCM. Consistent with the "Primacy-of-Warmth Effect" hypothesis, the study's findings show that perceived warmth, compared to perceived competence, is positively more associated with consumers' willingness to follow the VI's recommendations. Furthermore, the findings reveal that perceived warmth mediates the association between the VI's anthropomorphism and consumers' willingness to follow the VI's recommendations. However, the findings lend partial support to the mediating role of competence. The willingness to follow the VI's recommendations, in turn, is positively associated with purchase intention. The paper wraps up with some implications for research and practice.Scopu

Stereotyping human-like virtual influencers in retailing: Does warmth prevail over competence?

Building upon the Stereotype Content Model (SCM), the current research provides insights into how virtual influencers (VIs) influence consumer responses. More specifically, it investigates the associations between the VI's anthropomorphism and stereotypical judgments of the VI's warmth and competence as well as the differential and mediating roles of these stereotypes in influencing consumers' willingness to follow the VI's recommendations and purchase intentions. The results support the idea that anthropomorphizing VIs has a direct bearing on stereotyping VIs along the competence and warmth dimensions of the SCM. Consistent with the “Primacy-of-Warmth Effect” hypothesis, the study's findings show that perceived warmth, compared to perceived competence, is positively more associated with consumers' willingness to follow the VI's recommendations. Furthermore, the findings reveal that perceived warmth mediates the association between the VI's anthropomorphism and consumers' willingness to follow the VI's recommendations. However, the findings lend partial support to the mediating role of competence. The willingness to follow the VI's recommendations, in turn, is positively associated with purchase intention. The paper wraps up with some implications for research and practice

Working with ELSA – How an Emotional Support Agent Builds Trust in Virtual Teams

Virtual collaboration is an increasing part of daily life for many employees. Despite many advantages, however, virtual collaborative work can lead to a lack of trust among virtual team members, e.g., due to spatial separation and little social interaction. Previous findings indicated that emotional support provided by a conversational agent (CA) can impact human-agent trust and the perceived social presence. We developed an emotional support agent called ELSA and conducted a between-subject online experiment to examine how CAs can provide emotional support in order to increase the level of trust among colleagues in virtual teams. We found that human-agent trust positively influences the level of calculus-based trust among team members and increases team cohesion, whereas perceived anthropomorphism and social presence towards a CA seems to be less important for trust among team members

Artificial Companions with Personality and Social Role

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

A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers

Kulms P, Kopp S. A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers. Frontiers in Digital Humanities. Human-Media Interaction. 2018;5: 14.Trust is a crucial guide in interpersonal interactions, helping people to navigate through social decision-making problems and cooperate with others. In human–computer interaction (HCI), trustworthy computer agents foster appropriate trust by supporting a match between their perceived and actual characteristics. As computers are increasingly endowed with capabilities for cooperation and intelligent problem-solving, it is critical to ask under which conditions people discern and distinguish trustworthy from untrustworthy technology. We present an interactive cooperation game framework allowing us to capture human social attributions that indicate trust in continued and interdependent human–agent cooperation. Within this framework, we experimentally examine the impact of two key dimensions of social cognition, warmth and competence, as antecedents of behavioral trust and self-reported trustworthiness attributions of intelligent computers. Our findings suggest that, first, people infer warmth attributions from unselfish vs. selfish behavior and competence attributions from competent vs. incompetent problem-solving. Second, warmth statistically mediates the relation between unselfishness and behavioral trust as well as between unselfishness and perceived trustworthiness. We discuss the possible role of human social cognition for human–computer trust

Social Touch in Human-agent Interactions in an Immersive Virtual Environment

International audienceWorks on artificial social agents, and especially embodied conversational agents, have endowed them with social-emotional capabilities. They are being given the abilities to take into account more and more modalities to express their thoughts, such as speech, gestures, facial expressions, etc. However, the sense of touch, although particularly interesting for social and emotional communication, is still a modality widely missing from interactions between humans and agents. We believe that integrating touch into those modalities of interaction between humans and agents would help enhancing their channels of empathic communication. In order to verify this idea, we present in this paper a system allowing tactile communication through haptic feedback on the hand and the arm of a human user. We then present a preliminary evaluation of the credibility of social touch in human-agent interaction in an immersive environment. The first results are promising and bring new leads to improve the way humans can interact through touch with virtual social agents