Automated planning and scheduling (APS) is a process that employs artificial intelligence techniques to create plans and schedules for a given task or set of tasks. Automated planning applications (APAs) are software programs that use APS to generate plans and schedules for specific applications.
APS generates plans and schedules that fulfill specified objectives using task requirements and constraints. Search algorithms like A*, greedy search, and evolutionary algorithms are used as planning techniques. APS outputs a set of plans and schedules that can be used to execute the task. It can be scaled to handle complex tasks and integrated with other systems.
APAs, on the other hand, generate application-specific plans and schedules using APS. They use domain-specific heuristics in addition to search algorithms to generate plans and schedules. The input data includes application-specific information like task dependencies and resource availability. The output of APAs is a set of plans and schedules tailored to the specific needs of the application. They can be scaled to handle large, complex applications and integrated with other systems.
APS and APAs are useful in manufacturing, logistics, and healthcare applications. Examples of APS include the NASA Mars Rover mission and the DARPA Robotics Challenge. APAs are prevalent in healthcare applications such as scheduling appointments and allocating resources in hospitals.
In conclusion, APS and APAs are valuable tools for generating plans and schedules for complex tasks and applications. They use artificial intelligence techniques such as search algorithms and domain-specific heuristics to generate plans and schedules that fulfill the requirements of the task or application.
References:
Ghallab, M., Nau, D., & Traverso, P. (2016). Automated planning and acting. Cambridge University Press.
Fox, M., Long, D., & Magazzeni, D. (2017). Automated planning and scheduling. Springer.
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