Multi-Agent Deep Reinforcement Learning Audits Silver Futures Markets
A new technical implementation introduces a multi-agent audit engine leveraging double deep Q-networks to monitor strategic behaviour in the Silver futures market. The system uses advanced deep reinforcement learning and recent research to distinguish between competitive and potentially cooperative trading agent outcomes. Results indicate that during a recent sample window, market behaviors remained within normal competitive ranges rather than exhibiting signs of tacit coordination.