A sub field of artificial intelligence (AI) concerned with helping agents generate valid and coherent plans of actions to reach a goal.
Approaches were divided into state space planners and planning space planners. State space would be something like ‘the door is open’ where plan space would be ‘open the door’. Generally plan space planners are faster (there tends to be fewer actions than states) to search when looking for a solution.
One limitation is that problem domains for use with planning algorithms must be known in advance. This limits the applications to domains you can fully specify and isn’t resilient to change (e.g. the actions or effects change dynamically).
Another limitation is searching for an answer tended to be slow. For example, in the least efficient case a search for a plan devolves to an exhaustive, brute force search. GraphPlan is a much faster approach that generates graph data structure that trims the search space.
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From an entry point uncover all of the possible actions a user could take in a user interface. Actions are anything that causes the state of the application to change.