Emotions as Value Signals and Amplifiers: An Evolutionary and Computational Framework for Affective Experience in Biological and Artificial General Intelligence
The framework shows emotions guide survival decisions in biological and AI systems, suggesting enhancements for adaptive behavior.
Key Points
This research aims to illustrate emotions as evolutionarily essential signals that influence both biological organisms and artificial general intelligence.
Integrated concepts from evolutionary biology, neuroscience, and cognitive science.
Formulated a computational model of emotions and their roles as value signals.
Explored specific mechanics of emotional responses such as fear and love.
Emotions are identified as critical components in survival and decision-making processes.
Demonstrated how emotional analogs in AI can improve motivational depth and social alignment.
Addressed ethical considerations like manipulation and bias in emotional AI.