Authors:
Fernanda M. Eliott
and
Carlos H. C. Ribeiro
Affiliation:
Technological Institute of Aeronautics, Brazil
Keyword(s):
Biologically Inspired Architecture, Artificial Moral Machine, Reinforcement Learning.
Related
Ontology
Subjects/Areas/Topics:
Artificial Emotions and Emotional Intelligence
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computational Neuroscience
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Computation Issues in Social Behaviour Emergence
;
Neural Networks
;
Neurocomputing
;
Neuroinformatics and Bioinformatics
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
The extension of our integration to technologies brings about the possibility of inserting moral prototypes into artificial agents, no matter if they are going to interact with other artificial agents or biological creatures. We describe here MultiA, a computational model for simulating moral behavior derived from changes over a biologically inspired architecture. MultiA uses reinforcement learning techniques and is intended to produce selective cooperative behavior as a consequence of a biologically plausible model of morality inspired from a perusal of empathy. MultiA has its sensorial information translated into emotions and homeostatic variable values, which feed cognitive and learning systems. The moral behavior is expected to emerge from the artificial social emotion of sympathy and its associated feeling of empathy, based on an ability to internally emulate other agents internal states.