biostudies-literatureHernandez-Marcos AMCIN/AEI /10.13039/501100011033/ and FEDER Una manera de hacer Europa25858https://www.ebi.ac.uk/biostudies/studies/S-EPMC11519482biostudies-literatureUnknown14(1)In nature, intelligent living beings have developed emotions to modulate their behavior as a fundamental evolutionary advantage. However, researchers seeking to endow machines with this advantage lack a clear theory from cognitive neuroscience describing emotional elicitation from first principles, namely, from raw observations to specific affects. As a result, they often rely on case-specific solutions and arbitrary or hard-coded models that fail to generalize well to other agents and tasks. Here we propose that emotions correspond to distinct temporal patterns perceived in crucial values for living beings in their environment (like recent rewards, expected future rewards or anticipated world states) and introduce a fully self-learning emotional framework for Artificial Intelligence agentScientific reportsA generic self-learning emotional framework for machines.PMC11519482PID2022-140095NB-I00Hernandez-Marcos ARos EfalseA generic self-learning emotional framework for machines.In nature, intelligent living beings have developed emotions to modulate their behavior as a fundamental evolutionary advantage. However, researchers seeking to endow machines with this advantage lack a clear theory from cognitive neuroscience describing emotional elicitation from first principles, namely, from raw observations to specific affects. As a result, they often rely on case-specific solutions and arbitrary or hard-coded models that fail to generalize well to other agents and tasks. Here we propose that emotions correspond to distinct temporal patterns perceived in crucial values for living beings in their environment (like recent rewards, expected future rewards or anticipated world states) and introduce a fully self-learning emotional framework for Artificial Intelligence agent2024-01-01T00:00:00Z2024 Oct2025-04-04T02:35:53.071Z2025-04-04T02:35:53.071ZS-EPMC115194823946810910.1038/s41598-024-72817-x