Created: 2023-05-10 22:57
Significant progress in AI has been driven by insights into human perception, specifically the idea that Humans perceive the world as value and impedimate rather than objects.
As AI research shifted from rule-based systems and narrowly defined problems to goal-oriented agents, learning from interactions with their environment became central.
One such approach is Reinforcement learning, where AI agents learn to make decisions by maximizing cumulative rewards over time.
By adopting a perspective on perception that is similar to human behavior, AI systems have become more sophisticated and adaptable, contributing to rapid progress in the field.