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A Multidimensional Scaling Approach to Indexing by Metric Adaptation and Representation Upgrade

Following recent neurophysiological research, one important role of emotions consists in providing a mechanism for adequate and efficient response to relevant stimuli (Damasio 1994). In this paper we propose a methodology for implementing such a mechanism, based on a previously presented emotion-based agent model (Ventura & Pinto-Ferreira 1998). This model is founded on a double knowledge representation paradigm: a stimulus reaching the agent is processed under two different and simultaneous perspectives — a simple (termed perceptual) and a complex (termed cognitive) — from which two differing representation schemata are derived. The perceptual representation is oriented to capturing the relevant aspects of the environment, aiming at a quick response to urgent situations, while the cognitive one is directed towards high-level cognitive processing. These two representations are associated and stored in the agent memory in such a way that, in the future, if the agent is confronted with a similar situation, the perceptual representation will help the retrieval of the cognitive one in an efficient way. This indexing mechanism provides a quick algorithm to find cognitive matches. The indexing mechanism addressed in this paper was previously formulated and theoretically analyzed, under the assumption that the matching of the cognitive and perceptual images are performed in metric spaces (Ventura & PintoFerreira 2002). Given a stimulus s ∈ S, the agent extracts two kinds of representations: a perceptual image ip ∈ Ip, and a cognitive one ic ∈ Ic. Each one of the sets Ip and Ic of all possible perceptual and cognitive images is equipped with a metric function, denoted by dp : Ip × Ip → R0 and dc : Ic×Ic → R0 respectively, mapping pairs of images to distances, interpreted as degrees of mismatch. The memory is assumed to be formed by pairs of cognitive and perceptual images 〈ic , ip〉 (k = 1, . . .). The goal of the indexing mechanism is then to find the memory pair which cognitive image minimizes its distance to the one extracted from the stimulus, employing the perceptual representation to do so in an efficient manner. The research presented here concerns the following prob-