87,644 research outputs found

    Ambient intelligence in emotion based ubiquitous decision making

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    As the time goes on, it is a question of common sense to involve in the process of decision making people scattered around the globe. Groups are created in a formal or informal way, exchange ideas or engage in a process of argumentation and counterargumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this work it is proposed an agent-based architecture to support a ubiquitous group decision support system, i.e. based on the concept of agent, which is able to exhibit intelligent, and emotional-aware behaviour, and support argumentation, through interaction with individual persons or groups. It is enforced the paradigm of Mixed Initiative Systems, so the initiative is to be pushed by human users and/or intelligent agents

    Ambient intelligence in emotion based ubiquitous decision making

    Get PDF
    As the time goes on, it is a question of common sense to involve in the process of decision making people scattered around the globe. Groups are cre- ated in a formal or informal way, exchange ideas or engage in a process of argumentation and counter- argumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this work it is proposed an agent-based architecture to support a ubiquitous group decision support system, i.e. based on the concept of agent, which is able to exhibit intelli- gent, and emotional-aware behaviour, and support argumentation, through interaction with individual persons or groups. It is enforced the paradigm of Mixed Initiative Systems, so the initiative is to be pushed by human users and/or intelligent agents

    The Role of Emotions in Autonomous Social Agents

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    The holy grail of both AI and cognitive science is human-level intelligence. Whereas AI relies on computer algorithms to simulate human abilities, cognitive scientists investigate the brain to understand the underlying mechanisms. For most of human history, emotions were thought to be nothing more than disturbances for cognition. Therefore, they were usually ostracized from research on intelligence. As a result, cognitive architectures only partially include emotions in their design, if at all. Recently, though, it was discovered that emotions and cognition are in fact inter-dependent systems. Consequently, before being able to fully replicate human-level intelligence, it is necessary to understand the concept of emotions and its many roles within the brain. In this thesis, working around the lack of definition for emotion, I show that emotions inform the brain as to the nature of a given situation and guide the decision-making process, to increase the survival potential of virtual agents. In particular ProtoEmo, an architecture replicating the circuits found at the base of the forebrain, is shown to have the ability to detect stimuli relevant to the survival of virtual agents. Hence, it outperforms other emotional agents in terms of survival capabilities, which are measured by the size of the remaining population at the end of a resource foraging task. PrimEmo, the architecture born from the integration of ProtoEmo with standard models of the reward and decision-making systems in the brain, displays survival capabilities similar to the advantage actor-critic algorithm. PrimEmo also shows promises for supporting primitive emotions characterized by their level of arousal and valence. After further refinement, PrimEmo could replace the core decision-making module of a cognitive architecture, such as ACT-R or SOAR. Not only would it confer survival capabilities to the architecture, it would also allow for the possibility of investigating full-fledged emotions, and even emotional expression

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

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    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

    Integration of psychological models in the design of artificial creatures

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    Artificial creatures form an increasingly important component of interactive computer games. Examples of such creatures exist which can interact with each other and the game player and learn from their experiences. However, we argue, the design of the underlying architecture and algorithms has to a large extent overlooked knowledge from psychology and cognitive sciences. We explore the integration of observations from studies of motivational systems and emotional behaviour into the design of artificial creatures. An initial implementation of our ideas using the “sim agent” toolkit illustrates that physiological models can be used as the basis for creatures with animal like behaviour attributes. The current aim of this research is to increase the “realism” of artificial creatures in interactive game-play, but it may have wider implications for the development of AI

    Simulation of emotions of agents in virtual environments using neural networks

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    A distributed architecture for a system simulating the emotional state of an agent acting in a virtual environment is presented. The system is an implementation of an event appraisal model of emotional behaviour and uses neural networks to learn how the emotional state should be influenced by the occurrence of environmental and internal\ud stimuli. A part of the modular system is domain-independent. The system can easily be adapted for handling different events that influence the emotional state. A first\ud prototype and a testbed for this architecture are presented

    Motivations, Values and Emotions: 3 sides of the same coin

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    This position paper speaks to the interrelationships between the three concepts of motivations, values, and emotion. Motivations prime actions, values serve to choose between motivations, emotions provide a common currency for values, and emotions implement motivations. While conceptually distinct, the three are so pragmatically intertwined as to differ primarily from our taking different points of view. To make these points more transparent, we briefly describe the three in the context a cognitive architecture, the LIDA model, for software agents and robots that models human cognition, including a developmental period. We also compare the LIDA model with other models of cognition, some involving learning and emotions. Finally, we conclude that artificial emotions will prove most valuable as implementers of motivations in situations requiring learning and development

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

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    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

    Embodied Robot Models for Interdisciplinary Emotion Research

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    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
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