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

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

Sharing emotions and space - empathy as a basis for cooperative spatial interaction

Boukricha H, Nguyen N, Wachsmuth I. Sharing emotions and space - empathy as a basis for cooperative spatial interaction. In: Kopp S, Marsella S, Thorisson K, Vilhjalmsson HH, eds. Proceedings of the 11th International Conference on Intelligent Virtual Agents (IVA 2011). LNAI. Vol 6895. Berlin, Heidelberg: Springer; 2011: 350-362.Empathy is believed to play a major role as a basis for humans’ cooperative behavior. Recent research shows that humans empathize with each other to different degrees depending on several modulation factors including, among others, their social relationships, their mood, and the situational context. In human spatial interaction, partners share and sustain a space that is equally and exclusively reachable to them, the so-called interaction space. In a cooperative interaction scenario of relocating objects in interaction space, we introduce an approach for triggering and modulating a virtual humans cooperative spatial behavior by its degree of empathy with its interaction partner. That is, spatial distances like object distances as well as distances of arm and body movements while relocating objects in interaction space are modulated by the virtual human’s degree of empathy. In this scenario, the virtual human’s empathic emotion is generated as a hypothesis about the partner’s emotional state as related to the physical effort needed to perform a goal directed spatial behavior

A conceptual framework for interactive virtual storytelling

This paper presents a framework of an interactive storytelling system. It can integrate five components: management centre, evaluation centre, intelligent virtual agent, intelligent virtual environment, and users, making possible interactive solutions where the communication among these components is conducted in a rational and intelligent way. Environment plays an important role in providing heuristic information for agents through communicating with the management centre. The main idea is based on the principle of heuristic guiding of the behaviour of intelligent agents for guaranteeing the unexpectedness and consistent themes

Cognitive modeling of social behaviors

To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual mind as ways of carrying out activities. This requires for the psychologist a shift from only modeling goals and tasks —why people do what they do—to modeling behavioral patterns—what people do—as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). To illustrate these ideas, this article presents an extract from a Brahms simulation of the Flashline Mars Arctic Research Station (FMARS), in which a crew of six people are living and working for a week, physically simulating a Mars surface mission. The example focuses on the simulation of a planning meeting, showing how physiological constraints (e.g., hunger, fatigue), facilities (e.g., the habitat’s layout) and group decision making interact. Methods are described for constructing such a model of practice, from video and first-hand observation, and how this modeling approach changes how one relates goals, knowledge, and cognitive architecture. The resulting simulation model is a powerful complement to task analysis and knowledge-based simulations of reasoning, with many practical applications for work system design, operations management, and training

Towards a Model of Open and Reliable Cognitive Multiagent Systems: Dealing with Trust and Emotions

 Open multiagent systems are those in which the agents can enter or leave the system freely. In these systems any entity with unknown intention can occupy the environment. For this scenario trust and reputation mechanisms should be used to choose partners in order to request services or delegate tasks. Trust and reputation models have been proposed in the Multiagent Systems area as a way to assist agents to select good partners in order to improve interactions between them. Most of the trust and reputation models proposed in the literature take into account their functional aspects, but not how they affect the reasoning cycle of the agent. That is, under the perspective of the agent, a trust model is usually just a “black box” and the agents usually does not take into account their emotional state to make decisions as well as humans often do. As well as trust, agent’s emotions also have been studied with the aim of making the actions and reactions of the agents more like those of humans being in order to imitate their reasoning and decision making mechanisms. In this paper we analyse some proposed models found in the literature and propose a BDI and multi-context based agent model which includes emotional reasoning to lead trust and reputation in open multiagent systems

Normative Emotional Agents: a viewpoint paper

[EN] Human social relationships imply conforming to the norms, behaviors and cultural values of the society, but also socialization of emotions, to learn how to interpret and show them. In multiagent systems, much progress has been made in the analysis and interpretation of both emotions and norms. Nonetheless, the relationship between emotions and norms has hardly been considered and most normative agents do not consider emotions, or vice-versa. In this article, we provide an overview of relevant aspects within the area of normative agents and emotional agents. First we focus on the concept of norm, the different types of norms, its life cycle and a review of multiagent normative systems. Secondly, we present the most relevant theories of emotions, the life cycle of an agent¿s emotions, and how emotions have been included through computational models in multiagent systems. Next, we present an analysis of proposals that integrate emotions and norms in multiagent systems. From this analysis, four relationships are detected between norms and emotions, which we analyze in detail and discuss how these relationships have been tackled in the reviewed proposals. Finally, we present a proposal for an abstract architecture of a Normative Emotional Agent that covers these four norm-emotion relationships.This work was supported by the Spanish Government project TIN2017-89156- R, the Generalitat Valenciana project PROMETEO/2018/002 and the Spanish Goverment PhD Grant PRE2018-084940.Argente, E.; Del Val, E.; Pérez-García, D.; Botti Navarro, VJ. (2022). Normative Emotional Agents: a viewpoint paper. IEEE Transactions on Affective Computing. 13(3):1254-1273. https://doi.org/10.1109/TAFFC.2020.3028512S1254127313

Using the Myers-Briggs Type Indicator (MBTI) for Modeling Multiagent Systems

The formation of high-performance teams has been a constant challenge for organizations, which despite considering human capital as one of the most important resources, it still lacks the means to allow them to have a better understanding of several factors that influence the formation of these teams. In this sense, studies also demonstrate that teamwork has a significant impact on the results presented by organizations, in which human behavior is highlighted as one of the main aspects to be considered in the building of work teams. The Myers-Briggs Type Indicator seeks to classify the behavioral preferences of individuals around eight characteristics, which grouped as dichotomies, describe different psychological types. With it, researchers have sought to expand the ability to understand the human factor, using strategies with multiagent systems that, through experiments and simulations, using computer resources, enable the development of artificial agents that simulate human actions. In this work, we present an overview of the research approaches that use MBTI to model agents, aiming at providing a better knowledge of human behavior. Additionally, we make a preliminary discussion of how these results could be explored in order to advance the studies of psychological factors' influence in organizations' work teams formation