Hyper-Fast Parallel Q-Learning

Multiple Agents • High-Speed Processing • Zero Libraries

Neural Control

Agent Swarm Size 5

Processing Speed (Steps/Frame) 1

Exploration (ε) 0.2

Episodes

Total Steps

Unlike standard RL, this uses a "Swarm" of agents updating a shared Q-Table. This effectively implements a multi-threaded discovery process.

Higher "Steps/Frame" runs more logic per visual update, allowing the model to train thousands of times faster than real-time.