Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...

An AI agent reads its own source code, forms a hypothesis for improvement (such as changing a learning rate or an architecture depth), modifies the code, runs the experiment, and evaluates the results ...