Hybrid MARL-LP Approach: Building Scalable Logistics Scheduling
Stop chasing “God-Mode” AI agents. Ahmad Wael explains why a Hybrid MARL-LP Approach—combining Multi-Agent Reinforcement Learning with Linear Programming—is the only way to build a stable, scalable logistics scheduler. Learn how to separate strategy from physical constraints for faster inference and better generalization in complex networks.