Automated planning and scheduling: Difference between revisions

Revision as of 16:54, 21 April 2020

Revision as of 07:47, 14 May 2020

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== Overview ==

{{see|State space search}}

Given a description of the possible initial states of the world, a description of the desired goals, and a description of a set of possible actions, the planning problem is to synthesize a plan that is guaranteed (when applied to any of the initial states) to generate a state which contains the desired goals (such a state is called a goal state).

The difficulty of planning is dependent on the simplifying assumptions employed. Several classes of planning problems can be identified depending on the properties the problems have in several dimensions.

* Are the actions [[deterministic]] or nondeterministic? For nondeterministic actions, are the associated probabilities available?

* Are the [[state variablesvariable]]s discrete or continuous? If they are discrete, do they have only a finite number of possible values?

* Can the current state be observed unambiguously? There can be full observability and partial observability.

* How many initial states are there, finite or arbitrarily many?

* Do actions have a duration?

* Can several actions be taken concurrently, or is only one action possible at a time?

* Is the objective of a plan to reach a designated goal state, or to maximize a [[reward function]]?

* Is there only one agent or are there several agents? Are the agents cooperative or selfish? Do all of the agents construct their own plans separately, or are the plans constructed centrally for all agents?