NLP & ML3 min read
Research
Shared memory helps AI agents, but only until you hit five of them
Researchers shared replay buffers across actor-critic agents on parameterized action tasks. GAC jumped in performance, but SAC and TQC only crept forward. Beyond five agents, the computational cost climbs with no meaningful return. The paper offers a practical boundary for how far shared-experience methods can stretch before they stall.
2026-07-27