This repository implements constrained deep reinforcement learning for online 3D bin packing, a classic optimization problem in logistics and supply chain. The approach uses CNN-based state encoding and RL agents to learn placement policies for packing items into bins efficiently. It provides training and testing interfaces, supports lookahead scenarios, and includes comparison implementations like MCTS.