Abstract
We propose a method to investigate the adaptive and evolutionary function of emotions and affective states, in our case of ancestral fear - using Artificial Life and Evolutionary Robotics techniques. For this purpose, we developed a hybrid software-hardware capable to train artificial neuroagents equipped with a sensory-motor apparatus inspired on the iCub humanoid robot features. We trained populations of these agents throughout a genetic algorithm to perform a well-known neuropsychological task adapted to study emotional phenomena. The robots learnt to discriminate stressful emotional conditions (coping with “dangerous” stimuli) and no-stress conditions. Varying the network structures, the experimental conditions and comparing the outcomes we were able to delineate a very initial snapshot of behavioral and neural prerequisite for emotional-based actions. On the other hand, we have to stress that the main contribution we brought is setting-up a methodology to support future studies on emotions in natural and artificial agents.
DOI
10.1007/978-3-319-12745-3_5
Publication Date
2014-11-04
Publication Title
Communications in Computer and Information Science
Publisher
Springer International Publishing
ISBN
9783319127446
ISSN
1865-0937
Embargo Period
2024-11-22
First Page
47
Last Page
57
Recommended Citation
Pacella, D., Gigliotta, O., & Miglino, O. (2014) 'Studying the Evolutionary Basis of Emotions Through Adaptive Neuroagents: Preliminary Settings and Results', Communications in Computer and Information Science, , pp. 47-57. Springer International Publishing: Available at: https://doi.org/10.1007/978-3-319-12745-3_5
