Embodied Robot Models for Interdisciplinary Emotion Research

Due to their complex nature, emotions cannot be properly understood from the perspective of a single discipline. In this paper, I discuss how the use of robots as models is beneficial for interdisciplinary emotion research. Addressing this issue through the lens of my own research, I focus on a critical analysis of embodied robots models of different aspects of emotion, relate them to theories in psychology and neuroscience, and provide representative examples. I discuss concrete ways in which embodied robot models can be used to carry out interdisciplinary emotion research, assessing their contributions: as hypothetical models, and as operational models of specific emotional phenomena, of general emotion principles, and of specific emotion ``dimensions''. I conclude by discussing the advantages of using embodied robot models over other models.Peer reviewe

Conflicted Minds: Recalibrational Emotions Following Trust-based Interaction.

Consistent with a modular view of the mind, both short-sighted and long-sighted programs may be simultaneously active in the mind and in conflict with one another when individuals face choice dilemmas in trust-based economic interactions. Recalibrational theory helps us identify the adaptive design features shared among subsets of superordinate emotion programs. According to this design logic and the computation of adaptive problem features produced by Trust games, we predict the activation of emotions after Trust games. While this study successfully predicts reports of twenty distinct emotional states, further studies are needed to demonstrate ultimate recalibrational functions of emotions.emotions, recalibrational theory, modularity, Trust game, experiments

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems

START: A Bridge between Emotion Theory and Neurobiology through Dynamic System Modeling

Lewis proposes "reconceptualization" (p. 1) of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for over thirty years. This commentary summarizes some of these themes and points to areas of particularly active research in this area

Towards Learning ‘Self’ and Emotional Knowledge in Social and Cultural Human-Agent Interactions

Original article can be found at: http://www.igi-global.com/articles/details.asp?ID=35052 Copyright IGI. Posted by permission of the publisher.This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modeling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottomup approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.Peer reviewe

A Hierarchical Emotion Regulated Sensorimotor Model: Case Studies

Inspired by the hierarchical cognitive architecture and the perception-action model (PAM), we propose that the internal status acts as a kind of common-coding representation which affects, mediates and even regulates the sensorimotor behaviours. These regulation can be depicted in the Bayesian framework, that is why cognitive agents are able to generate behaviours with subtle differences according to their emotion or recognize the emotion by perception. A novel recurrent neural network called recurrent neural network with parametric bias units (RNNPB) runs in three modes, constructing a two-level emotion regulated learning model, was further applied to testify this theory in two different cases.Comment: Accepted at The 5th International Conference on Data-Driven Control and Learning Systems. 201

Autonomic regulation in response to stress : the influence of anticipatory emotion regulation strategies and trait rumination

According to the neurocognitive framework for regulation expectation, adaptively regulating emotions in anticipation of a stressful event should help individuals deal with the stressor itself. The goal of this study was twofold: first, the authors compared the influence of adaptive versus maladaptive anticipatory emotion regulation (ER) on the autonomic system during anticipation of, confrontation with, and recovery from a stressor; second, they explored whether trait rumination moderated this relationship. The authors collected data from 56 healthy female undergraduates during a public speaking task. The task involved 4 phases: baseline, anticipatory ER, stressor, and recovery. Participants were assigned to 1 of 2 anticipatory ER instructions (reappraisal or catastrophizing). Heart rate variability (HRV) indexed autonomic regulation. Results confirmed that HRV was higher in the reappraisal than in the catastrophizing group (over all time points, except for baseline). Trait rumination levels moderated the effect of anticipatory ER strategy on HRV during the stressor phase. Specifically, whereas for low ruminators reappraisal (versus catastrophizing) in the anticipation phase led to higher HRV when confronted to the stressor, high ruminators demonstrated lower HRV in that same condition. To conclude, over all participants, using reappraisal during the anticipation phase allowed participants to better cope with stress. However, only low, but not high ruminators could profit from the beneficial effect of anticipatory reappraisal on autonomic regulation. Even though further research is needed, this study suggests that, in female undergraduates, the tendency to ruminate is associated with abnormal anticipatory ER that might hinder an adaptive response to a stressor

Network destabilization and transition in depression : new methods for studying the dynamics of therapeutic change

The science of dynamic systems is the study of pattern formation and system change. Dynamic systems theory can provide a useful framework for understanding the chronicity of depression and its treatment. We propose a working model of therapeutic change with potential to organize findings from psychopathology and treatment research, suggest new ways to study change, facilitate comparisons across studies, and stimulate treatment innovation. We describe a treatment for depression that we developed to apply principles from dynamic systems theory and then present a program of research to examine the utility of this application. Recent methodological and technological developments are also discussed to further advance the search for mechanisms of therapeutic change