A Cognitive Architecture for the Implementation of Emotions in Computing Systems
This work addresses the challenge of integrating affective phenomena into AI systems, potentially enabling more human-like computing, but it appears incremental as it builds on existing models like the Lövheim Cube.
The authors tackled the problem of implementing emotions in computing systems by proposing NEUCOGAR, a neurobiologically-inspired cognitive architecture that maps neuromodulators like dopamine to Von Neumann computing processes, and they validated it through simulations showing increased computing power and storage redistribution due to emotional stimuli.
In this paper we present a new neurobiologically-inspired affective cognitive architecture: NEUCOGAR (NEUromodulating COGnitive ARchitecture). The objective of NEUCOGAR is the identification of a mapping from the influence of serotonin, dopamine and noradrenaline to the computing processes based on Von Neuman's architecture, in order to implement affective phenomena which can operate on the Turing's machine model. As basis of the modeling we use and extend the Lövheim Cube of Emotion with parameters of the Von Neumann architecture. Validation is conducted via simulation on a computing system of dopamine neuromodulation and its effects on the Cortex. In the experimental phase of the project, the increase of computing power and storage redistribution due to emotion stimulus modulated by the dopamine system, confirmed the soundness of the model.