Responding efficiently to relevant stimuli using an emotion-based agent architecture $ Rodrigo Ventura à , Carlos Pinto-Ferreira Institute for Systems and Robotics, Instituto Superior Te´cnico, TULisbon, Lisbon, Portugal article info Available online 8 April 2009 Keywords: Emotions Relevance Autonomous agents abstract It is widely accepted that one important role of emotions consists in providing a mechanism for adequate and efficient response to relevant stimuli. In this paper we propose a methodology for implementing such a mechanism, based on a previously presented emotion-based agent model. This agent model is biologically inspired in the emotion mechanisms found in the brain, following recent neurophysiological research. This model is founded on two principles: (1) stimuli is represented internally by two representations with different degrees of complexity and accuracy, and (2) the matching of these representations is implemented by a distance function. The mechanism considered in this paper amounts to matching the current stimulus the agent is perceiving with its past experience. This paper addresses a twofold strategy for optimizing the efficiency and accuracy of this mechanism. The first one consists in adapting the distance function employed in one of the representations, while the second one has the goal of upgrading that representation with new relevant features. Techniques borrowed from nonmetric multidimensional scaling are used to approach these goals. & 2009 Elsevier B.V. All rights reserved. 1. Introduction When facing the design of intelligent agents, it is inevitable to consider human intelligence, for it provides the only a priori natural model of intelligence. Human intelligence, in a broad sense, involves two major capabilities: appropriate communica- tion, and appropriate decision-making. That emotions play a role in human communication is unquestionable: the expression of affect, the sensitivity to the affective state of others, the difficulty of faking emotions (e.g., actors often induce in themselves the emotions they need to display, in order for those emotional states to be believable). However, human–computer interface is tradi- tionally a cold one, where the computer is completely insensitive to the user’s emotional state (e.g., user frustration). The idea of changing this state of affairs was first proposed by Picard, while coining the word for the affective computing field: ‘‘computing that relates to, arises from, or deliberately influences emotions’’ [1]. The role that emotions play in appropriate decision-making is, however, more controversial. One source of controversy derives from the folk conception opposing sound and cold reasoning about an issue, and being emotional about it. Emotions are often considered a threat to the goodness of cold reasoning. Recent neuroscientific evidence has however undermined that idea: the emotional mechanisms of the brain prove to be essential for appropriate decision making. Research by Da ´ masio and colleagues report that patients with lesions in the prefrontal cortex show a severe impairment, for instance, in feeling emotions after being exposed to emotionally strong pictures. These patients, that nevertheless are able to perform in I.Q. tests within average, display a striking inability to perform simple, daily-life tasks. They report the case of a patient taking disproportionally long periods of time making his mind about scheduling his next encounter with the physician that has been following his case. Further research by Da ´ masio has allowed him to assemble an explanation: the somatic marked hypothesis (SMH). According to this hypothesis, decision-making in normal individuals is assisted by ‘‘the appearance of a somatic signal that marks the ultimate consequences of the response option with a negative or positive somatic state’’ [2, p. 220]. These somatic signals can be either conscious or covert, but they are physically measurable in general. One such common measure is the change in skin conductance, termed skin conductance responses (SCR). Conscious effects of this somatic marking are, for instance, the ‘‘gut feeling’’ when certain response options are considered. Covert effects include appetitive or aversive behaviors towards/away certain response options [2]. This paper presents an agent model originally inspired by Dama ´sio’s SMH. However, it should be stressed that the goal of this research is not the emulation of human emotions, but rather ARTICLE IN PRESS Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/neucom Neurocomputing 0925-2312/$ - see front matter & 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.neucom.2008.09.019 $ This work was partially supported by FCT (ISR/IST plurianual funding) through the POS-Conhecimento Program that includes FEDER funds. à Corresponding author. Tel.: +351218418195; fax: +351218418291. E-mail address: yoda@isr.ist.utl.pt (R. Ventura). Neurocomputing 72 (2009) 2923–2930