Recent neurological studies indicate that the role of emotion in human cognition is essential; emotions are not a luxury. Instead, emotions play a critical role in rational decision-making, in perception, in human interaction, and in human intelligence. These facts, combined with abilities computers are acquiring in expressing and recognizing affect, open new areas for research. This paper defines key issues in "affective computing," computing that relates to, arises from, or deliberately influences emotions. New models are suggested for computer recognition of human emotion, and both theoretical and practical applications are described for learning, human-computer interaction, perceptual information retrieval, creative arts and entertainment, human health, and machine intelligence. Significant potential advances in emotion and cognition theory hinge on the development of affective computing, especially in the form of wearable computers. This paper establishes challenges and future directions for this emerging field.

This paper focuses on the role of emotion and expressive behavior in regulating social interaction between humans and expressive anthropomorphic robots, either in communicative or teaching scenarios. We present the scientific basis underlying our humanoid robot's emotion models and expressive behavior, and then show how these scientific viewpoints have been adapted to the current implementation. Our robot is also able to recognize affective intent through tone of voice, the implementation of which is inspired by the scientific findings of the developmental psycholinguistics community. We first evaluate the robot's expressive displays in isolation. Next, we evaluate the robot's overall emotive behavior (i.e. the coordination of the affective recognition system, the emotion and motivation systems, and the expression system) as it socially engages nave human subjects face-to-face.

We present Cathexis, a distributed, computational model which offers an alternative approach to model the dynamic nature of different affective phenomena, such as emotions, moods and temperaments, and provides a flexible way of modeling their influence on the behavior of synthetic autonomous agents. The model has been implemented as part of an extensible, object-oriented framework which provides enough functionality for agent developers to design emotional agents that can be used in a variety of applications including entertainment (e.g. synthetic agents for interactive drama, video games, etc.), education (e.g. Intelligent Tutoring Systems), and human-computer interfaces.

This paper discusses the issues pertinent to the development of a meaningful social interaction between robots and people through employing degrees of anthropomorphism in a robot's physical design and behaviour. As robots enter our social space, we will inherently project/impose our interpretation on their actions similar to the techniques we employ in rationalising for example, a pet's behaviour. This propensity to anthropomorphise is not seen as a hindrance to social robot development, but rather a useful mechanism that requires judicious examination and employment in social robot research.

We describe an agent architecture that integrates emotions, drives, and behaviors, and that focuses on modeling some of the aspects of emotions as fundamental components within the process of decision-making. We show how the mechanisms of primary emotions can be used as building blocks for the acquisition of emotional memories that serve as biasing mechanisms during the process of making decisions and selecting actions. The architecture has been implemented into an object-oriented framework that has been successfully used to develop and control several synthetic agents and which is currently being used as the control system for an emotional pet robot. Introduction The traditional view on the nature of rationality has proposed that emotions and reason do not mix at all. For an agent to act rationally, it should not allow emotions to intrude in its reasoning processes. Research in Neuroscience, however, has provided evidence indicating quite the contrary, showing that emotions play a f...

Prototypes of interactive computer systems have been built that can begin to detect and label aspects of human emotional expression, and that respond to users experiencing frustration and other negative emotions with emotionally supportive interactions, demonstrating components of human skills such as active listening, empathy, and sympathy. These working systems support the prediction that a computer can begin to undo some of the negative feelings it causes by helping a user manage his or her emotional state. This paper clarifies the philosophy of this new approach to human-computer interaction: deliberately recognising and responding to an individual user’s emotions in ways that help users meet their needs. We define user needs in a broader perspective than has been hitherto discussed in the HCI community, to include emotional and social needs, and examine technology’s emerging capability to address and support such needs. We raise and discuss potential concerns and objections regarding this technology, and describe several opportunities for future work.

Abstract. We describe an Affect and Belief Adaptive Interface System (ABAIS) designed to compensate for performance biases caused by users ’ affective states and active beliefs. The ABAIS architecture implements an adaptive methodology consisting of four steps: sensing/inferring user affective state and performance-relevant beliefs; identifying their potential impact on performance; selecting a compensatory strategy; and implementing this strategy in terms of speci¢c GUI adaptations. ABAIS provides a generic adaptive framework for integrating a variety of user assessment methods (e.g. knowledge-based, self-reports, diagnostic tasks, physiological sensing), and GUI adaptation strategies (e.g. content- and format-based). The ABAIS performancebias prediction isbased on empirical ¢ndings from emotion research combined with detailed knowledge of the task context.The initial ABAIS prototype was demonstrated in the context of an Air Force combat task, used a knowledge-based approach to assess the pilot’s anxiety level, and adapted to the pilot’s anxiety and belief states by modifying selected cockpit instrument displays in response to detected changes in these states.

This paper discusses the role that synthetic emotions could play in building autonomous robots which engage people in human-style social exchange. We present a control architecture which integrates synthetic emotions and highlight how they influence the internal dynamics of the robot’s controller — biasing attention, motivation, behavior, learning, and the expression of motor acts. We present results illustrating how this control architecture, embodied within an expressive robot and situated in a social environment, enables the robot to socially influence its human caregiver into satisfying its goals.

This paper presents ongoing work towards building an autonomous robot that learns in a social context. The mode of

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