A Review of Agent Emotion Architectures

2010

Characters in games and virtual worlds continue to gain improvements in both their visual appearance and more human-like behaviours with each successive generation of hardware. One area that seemingly would need to be addressed if this evolution in human-like characters is to continue is in the area of characters with emotions. To begin addressing this, the thesis focuses on answering the question "Can an emotional architecture be developed for characters in games and virtual worlds, that is built upon a foundation of formal psychology? Therefore a primary goal of the research was to both review and consolidate a range of background material based on the psychology of emotions to provide a cohesive foundation on which to base any subsequent work. Once this review was completed, a range of supplemental material was investigated including computational models of emotions, current implementations of emotions in games and virtual worlds, machine learning techniques suitable for implementing aspects of emotions in characters in virtual world, believability and the role of emotions, and finally a discussion of interactive characters in the form of chat bots and non-player characters. With these reviews completed, a synthesis of the research resulted in the defining of an emotion architecture for use with pre-existing agent behaviour systems, and a range of evaluation techniques applicable to agents with emotions. To support validation of the proposed architecture three case studies were conducted that involved applying the architecture to three very different software platforms featuring agents. The first was applying the architecture to combat bots in Quake 3, the second to a chat bot in the virtual world Second Life, and the third was to a web chat bot used for e-commerce, specifically dealing with question and answers about the companies services. The three case studies were supported with several small pilot evaluations that were intended to look at different aspects of the implemented architecture including; (1) Whether or not users noticed the emotional enhancements. Which in the two small pilot studies conducted, highlighted that the addition of emotions to characters seemed to affect the user experience when the encounter was more interactive such as in the Second Life implementation. Where the interaction occurred in a combat situation with enemies with short life spans, the user experience seemed to be greatly reduced. (2) An evaluation was conducted on how the combat effectiveness of combat bots was affected by the addition of emotions, and in this pilot study it was found that the combat effectiveness was not quite statistically reduced, even when the bots were running away when afraid, or attacking when angry even if close to death. In summary, an architecture grounded in formal psychology is presented that is suitable for interactive characters in games and virtual worlds, but not perhaps ideal for applications

In this paper we describe our work in progress for exploring the role of emotions in the behaviour and decision-making of artificial agents in modeling and simulation systems. The computational model of emotions we are using is based on a multi-level theory of emotions that accounts for the three layers identified in the human emotional system: the sensory-motor level, the schematic level and the conceptual level. Our current interest lies in modeling and simulating the impact of emotions in the workplace, both at the individual and at the group level. We are working to incorporate our model of emotions into Brahms, a multi-level modeling and simulation system being developed at NASA Ames Research Center.

Abstract Several computational models of emotions have been proposed based on different approaches. Biologically inspired models developed generally for robots, consider a bottom-up approach whereas virtual agents are often based on a top-down approach. In this paper, we explore these two approaches. For the top-down approach, we analyze more particularly the problematic of virtual character's expression of emotions that should be in accordance with the social context.

Artificial Intelligence Review, 2012

A great number of computational models of emotions (CMEs) have been developed to be included in, or as part of, cognitive agent architectures. These computational models have been designed to provide autonomous agents with appropriate mechanisms for the processing of emotional stimuli, the elicitation of synthetic emotions, and the generation of emotional responses. The research on CMEs has allowed for improvements in several application domains and contributed to progress in areas such as human-computer interaction and artificial intelligence. Nevertheless, despite the wide variety of CMEs proposed in the literature and their success in multiple areas, the complexity and quality of current and future human-centered applications require the development of more flexible and robust CMEs. In this sense, CMEs have yet to face a series of challenges in order to meet such types of requirements. In this paper, we explore key aspects of the development and applications of CMEs for autonomous agents, discuss four major challenges facing their development process, and present a novel approach to deal with these challenges. Keywords Emotions • Computational modeling • Agent architectures • Affective agents 1 Introduction The multidisciplinary study of human emotions has led to the formulation of a great volume of theories and models that explain the various facets of this human function. These theories suggest that emotions play an important role in the development of rational behavior in humans and that experiencing and expressing them are essential for survival purposes. According to Damasio (1994) and Loewenstein and Lerner (2003), emotions influence human cognitive

Cognitive Computation, 2014

It has been recognized that human behavior is an observable consequence of the interactions between cognitive and affective functions. This perception has motivated the study of human emotions in disciplines such as psychology and neuroscience and led to the formulation of a number of theories and models that attempt to explain the mechanisms underlying this human process. In the field of artificial intelligence, these theoretical findings have posed a series of challenges in the development of autonomous agents (AAs) capable of exhibiting very believable and human-like behaviors. One of these challenges is the design and implementation of computational models of emotions (CMEs), which are software systems designed to provide AAs with proper mechanisms for the processing of emotional information, elicitation of synthetic emotions, and generation of emotional behaviors. In this paper, we review this type of computational model from the perspective of their development. Particularly, we investigate five design aspects that influence their development process: theoretical foundations, operating cycle, interaction between cognition and emotion, architectural design, and role in cognitive agent architectures. We provide discussions about key issues and challenges in the development of CMEs and suggest research that may lead to more robust and flexible designs for this type of computational model.

The Florida AI Research Society Conference, 2001

The role of emotions in intelligent behaviour has often been discussed: are emotions an essential part of the human intelli- gence machinery'? Recent research on the neurophysiology of human emotions suggests that human decision-making effi- ciency depends deeply on the emotions mechanism. In partic- ular. Ant6nio Dam~isio has proposed that alternative courses of action in a decision-making problem are emotionally

Procedia Computer Science, 2014

Game AI agents today do not reflect the affective aspects of human behavior. In particular, game agents do not reflect the effects of human emotional state on an agent's decision-making behavior. In rare instances when emotional aspects are addressed in game agent architectures, such behavior tends to be ad hoc and not informed by an underlying theory of emotion, nor validated using actual data. This paper presents a new emotional game agent architecture that is based on an underlying theory of emotion and validated by limited experiments. This architecture manifests a range of emotional effects on game agent behaviors. The overall approach is informed by both appraisal and dimensional theories of emotion. The combination of these theories as underpinnings ensures that emotionally appraised concepts in memory are reflected in the emotional state of the agent, and that such correspondence produces realistic emotional effects on the agent's decision-making behavior. The approach is validated through a series of increasingly more sophisticated experiments, in terms of scenario complexity and methods employed. The results are correlated with human data from previous cognitive science experiments. The results show that "lightweight" intelligent agents based on the new game agent architecture can exhibit realistic emotional behavior in real-time decision-making situations encountered in games across various domains.

2001

Emotions play a critical role in creating engaging and believable characters to populate virtual worlds. Our goal is to create general computational models to support characters that act in virtual environments, make decisions, but whose behavior also suggests an underlying emotional current. In service of this goal, we integrate two complementary approaches to emotional modeling into a single unified system. Gratch's Émile system focuses on the problem of emotional appraisal: how emotions arise from an evaluation of how environmental events relate to an agent's plans and goals. Marsella et al.'s IPD system focuses more on the impact of emotions on behavior, including the impact on the physical expressions of emotional state through suitable choice of gestures and body language. This integrated model is layered atop Steve, a pedagogical agent architecture, and exercised within the context of the Mission Rehearsal Exercise, a prototype system designed to teach decision-making skills in highly evocative situations.