ABSTRACT
The proposed invention introduces an Ant Colony Optimization (ACO) and Reinforcement Learning (RL)-based Task Scheduling and Assignment System, integrating Q-Learning and SARSA (State-Action-Reward-State-Action) algorithms to optimize workload distribution and task execution efficiency. The system leverage...