Job interview simulation with a virtual agents aims at improving people's social skills and supporting professional inclusion. In such simulators, the virtual agent must be capable of representing and reasoning about the user's mental state based on social cues that inform the system about his her affects and social attitude. In this paper, we propose a formal model of Theory of Mind (ToM) for virtual agent in the context of human-agent interaction that focuses on the affective dimension. It relies on a hybrid ToM that combines the two major paradigms of the domain. Our framework is based on modal logic and inference rules about the mental states, emotions and social relations of both actors. Finally, we present preliminary results regarding the impact of such a model on natural interaction in the context of job interviews simulation.
In order to be able to reason on the affective dimension of the interaction, conveyed by the non-verbal behaviour of both interlocutors, several models rely on the cognitive structure of emotions and appraisal theories such as CPM @cite_4 or OCC @cite_7 . These theories provide domain-independant descriptions of triggering conditions of emotions, that are required for the development the affective aspect of the ToM reasoner. For instance, @cite_14 @cite_13 are BDI-based implementation of the OCC theory. FAtiMA's double appraisal model @cite_18 , although not implemented using a BDI framework, also encodes the OCC model. However, in these models, the inference mechanism itself encodes the chosen Appraisal Theory. On the contrary, in our model, we propose a theory-independant ToM reasoner. While our experiments were conducted using an OCC-based model, the corresponding rules (described in equation ) could be easily replaced by another theory.
@cite_18 @cite_14 @cite_4 @cite_7 @cite_13
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We report the implementation and evaluation of a Simulation Theory (ST) approach to the Theory of Mind in intelligent graphical agents driven by an affective agent architecture FAtiMA. The existing cognitive appraisal mechanism is adapted to produce a second appraisal cycle, a double appraisal, in order to evaluate the emotional impact of possible actions. The action with the greatest emotional impact is selected as a means of producing more interesting dramatic actions. A variant in which the actual minds of characters present are used is also implemented and evaluated. Results show that these mechanisms do produce more interesting stories. This article discusses a formal belief, desire, intention (BDI)-based agent model for theory of mind (ToM). The model uses BDI concepts to describe the reasoning process of an agent that reasons about the reasoning process of another agent, which is also based on BDI concepts. We discuss three different application areas and illustrate how the model can be applied to each of them. We explore a case study for each of the application areas and apply our model to it. For each case study, a number of simulation experiments are described, and their results are discussed. 1. Introduction The study of emotion Types of evidence for theories of emotion Some goals for a cognitive theory of emotion 2. Structure of the theory The organisation of emotion types Basic emotions Some implications of the emotions-as-valenced-reactions claim 3. The cognitive psychology of appraisal The appraisal structure Central intensity variables 4. The intensity of emotions Global variables Local variables Variable-values, variable-weights, and emotion thresholds 5. Reactions to events: I. The well-being emotions Loss emotions and fine-grained analyses The fortunes-of-others emotions Self-pity and related states 6. Reactions to events: II. The prospect-based emotions Shock and pleasant surprise Some interrelationships between prospect-based emotions Suspense, resignation, hopelessness, and other related states 7. Reactions to agents The attribution emotions Gratitude, anger, and some other compound emotions 8. Reactions to objects The attraction emotions Fine-grained analyses and emotion sequences 9. The boundaries of the theory Emotion words and cross-cultural issues Emotion experiences and unconscious emotions Coping and the function of emotions Computational tractability. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements. Emotion communication research strongly focuses on the face and voice as expressive modalities, leaving the rest of the body relatively understudied. Contrary to the early assumption that body movement only indicates emotional intensity, recent studies have shown that body movement and posture also conveys emotion specific information. However, a deeper understanding of the underlying mechanisms is hampered by a lack of production studies informed by a theoretical framework. In this research we adopted the Body Action and Posture (BAP) coding system to examine the types and patterns of body movement that are employed by 10 professional actors to portray a set of 12 emotions. We investigated to what extent these expression patterns support explicit or implicit predictions from basic emotion theory, bidimensional theory, and componential appraisal theory. The overall results showed partial support for the different theoretical approaches. They revealed that several patterns of body movement systematically occur in portrayals of specific emotions, allowing emotion differentiation. Although a few emotions were prototypically expressed by one particular pattern, most emotions were variably expressed by multiple patterns, many of which can be explained as reflecting functional components of emotion such as modes of appraisal and action readiness. It is concluded that further work in this largely underdeveloped area should be guided by an appropriate theoretical framework to allow a more systematic design of experiments and clear hypothesis testing.