Automated Planning and Scheduling
Automated planning and scheduling is a significant branch of artificial intelligence focused on devising strategies or sequences of actions for intelligent agents, autonomous robots, and unmanned vehicles to achieve specific goals. This field addresses problems where the solution involves a series of decisions that must be made in such a way that a particular objective is reached under certain constraints.
Unlike straightforward control or classification tasks, planning and scheduling problems require navigating through a complex space of possible action sequences to find an optimal or satisfactory plan. This involves considering various factors such as resource constraints, temporal constraints, and interdependencies between actions.
Automated planning and scheduling systems use a variety of AI techniques, including search algorithms, optimization methods, and heuristic approaches to generate, evaluate, and select action sequences that meet the defined objectives and constraints.
In logistics and supply chain management, automated planning and scheduling systems can optimize the routing and scheduling of delivery vehicles to minimize travel time and fuel consumption while ensuring timely deliveries. For instance, an AI planning system can take into account traffic conditions, vehicle capacities, delivery time windows, and other logistical constraints to generate efficient routes for a fleet of delivery trucks.
Another application is in space missions, where automated planning and scheduling systems are used to manage the activities of spacecraft and rovers. For example, NASA's Mars rovers are equipped with AI planning software that helps them decide how to spend their time each day, choosing among various activities such as traveling, examining rock samples, and capturing images. The rover's planning system must account for energy constraints, communication windows with Earth, and the scientific value of potential tasks to create a daily schedule that maximizes the mission's scientific return.