From the source
The Era of Multi-Agent Imagined Experience Why the next leap in machine intelligence won't be learned alone—it will be learned by agents playing, competing, and cooperating inside world models Ahmet Hamdi Guzel June 12th, 2026 The Story of Modern AI in Three Acts In the first act, the era of self-play, agents learned by trial and error inside closed worlds with a single, crisp objective.
This is the era that gave us superhuman play in backgammon, Go, chess, and Atari—agents that discovered strategies no human had taught them.
In the second act, the era of imitation, the field pivoted to imitation: train on the vast corpus of everything people have written and said, and a single model inherits a startling breadth of competence.
This is the era of the large language model.
David Silver and Richard Sutton have argued, persuasively, that we are now entering a third act: the era of experience .
Imitation can reproduce what people already know, but it struggles to exceed it.
To go further, agents need to generate their own data—to act, observe the consequences, and improve from grounded signals in their environment rather than from human pre-judgment.
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