The Exploitation of Models in Artificial Emotions

The Exploitation of Models in Artificial Emotions

M.G. Sánchez-Escribano, Carlos Herrera, Ricardo Sanz
DOI: 10.4018/978-1-4666-7278-9.ch006
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Cognitive processes might be seen as reciprocal items and they are usually characterized by multiple feedback cycles. Emotions constitute one major source of feedback loops to assure the maintenance of well-being, providing cognitive processes with quantifiable meaning. This suggests the exploitation of models to improve the adaptation under value-based protocols. Emotion is not an isolated effect of stimuli, but it is the set of several effects of the stimuli and the relationships among them. This chapter proposes a study of the exploitation of models in artificial emotions, pointing out relationships as part of the model as well as the model exploitation method.
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Overview On Biological Emotion Research

The structural and funcional models from the perspective of biological emotion can be summarized into two major approaches: a) the physiological perspective, focused on the structural basis within the brain, and b) the psychological perspective, addressing the emotional phenomenon within the agent (The psychologist's point of view refers the study of emotion as an intrapersonal process (Fridja, 2008))

The analysis of the physiological changes of bodily subsystems during emotional processes, provides sets of data over which to explain the physical origin and extent of the emotions. The classic vision of W. James (1884) that afterwards was detailed by (Lange et al., 1922), shows emotion as mental representation of body responses to relevant stimuli. It was also refined by Cannon and Bard (Cannon et. al, 1927) arguing a simultaneous approach to the physiological change, and whose effects have the origin in the hypothalamus region of the brain. Analogously, the initial approaches of Pápez (1937) suggested the distributed nature of the emotional processes in his dual circuit model, and the works of Klüver and Bucy (Klüver et. al, 1937), McLean (McLean, 1990) and LeDoux (1996; 2000) showed that this structure is not so clearly delimited in the brain as it might seem.

Key Terms in this Chapter

Context: It refers to those circumstances, conditions, factors, state of affairs, situation, background, scene, etc. that affects the system within its domain .

Artificial Agent: It is used to refer to any software program but recognizing that, in general, there are many more classes of agent implementations. Some Artificial Agent might be designated Intelligent Agent , Cognitive Agent , Autonomous Agent , etc. concerning its functional possibilities. The term Cognitive Agent is used to refer agents with aptitude to exploit knowledge. If some Cognitive Agent implements Artificial Emotion , it is named Emotional Agent .

Domain: Includes the portion of the environment that is relevant for the system concerning its operational state; any change in the domain brings about significant events that affect the system operation. The emergence of new requirements is due to the enactment of a new subset of the entire domain that becomes relevant for the system at a given time.

Model: In a generic definition it is an information entity corresponding with a system in a formal relationship that condenses several essential features to define the system . Commonly, systems need models to incorporate usable knowledge concerning the structural and functional baselines of readiness operative. Models are abstractions of reality that contain just the essential aspects of this reality concerning the system ( Selic, 2003 ). The function of a model regards both the interpretation and the understanding of the system, as well as the drawing of conclusions in the form of other subsequent and usable models. This work proposes to build models that provide causal connections with the inner context of the system at runtime.

Exploitation: The exploitation refers to any system operation in which by making use of model resources, optimizes each operational phase within the system. It is also related with the improvement of models by using the empirical base on experience and observation, rather than inferences or built code.

Agent: It refers the whole entity with aptitude to do something.

System: It is a set of entities and relationships . Usually systems operate in order to reach some concrete goal. We may speack of both a system of agents as well as of the system of the agent to refer to the agent realization itself.

System (Automonous System): It is a system that operates connecting its internal dynamics with the dynamic of its environment in the context of the performance of task.

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