Multi-Agent Learning with Cooperation-Driven Optimization Dynamics
The results support the claim that several small agents can outperform a single large model on a given classification task; the shared signals affect each agent's optimization algorithm by modulating both the descent direction and the step size, converging toward a global consensus.
Jarod Ketcha Kouakep, Sreyvi Uann, Timoteo Carletti
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