d sequentially in a random path, the environment generates the states for each grid node, and feeds the state to the actor and critic agents that respectively predict and evaluate the updated property of the grid node The data is stored in a replay memory, which is sampled at regular intervals to train the agents. The trained agents are then used for further rounds of self-learning. An application of the proposed algorithm at a copper mining operation with incoming drilling machine sensor data (collected spatially), and processing mill sensor data (collected over time), demonstrates its applie