Automated Planning Task

AKA: Automated Scheduling.
Context:
- It can be solved by an Automated Planning System (that applies an automated planning algorithm).
See: Action Language, Unmanned Vehicle, Control System, Decision Theory, Trial and Error, POMDP.

References

(Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/automated_planning_and_scheduling Retrieved:2017-8-1.
- Automated planning and scheduling, sometimes denoted as simply AI Planning, is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space. Planning is also related to decision theory.
  In known environments with available models, planning can be done offline. Solutions can be found and evaluated prior to execution. In dynamically unknown environments, the strategy often needs to be revised online. Models and policies must be adapted. Solutions usually resort to iterative trial and error processes commonly seen in artificial intelligence. These include dynamic programming, reinforcement learning and combinatorial optimization. Languages used to describe planning and scheduling are often called action languages.

(Bonet & Geffner, 2001) ⇒ Blai Bonet, and Héctor Geffner. (2001). “Planning as Heuristic Search.” In: Artificial Intelligence, 129(1).