Planning Systems in Artificial Intelligence

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Planning is a useful application in artificial intelligence field. It can be applied to solve many practical problems in various fields such as In manufacturing : reconfiguration production line in order to increase flexibility of the production line, In government service: schedule the train to maximize customer satisfaction. Etc. This paper overviews some idea of the classical and reactive planning. The classical planning assumes that the initial world does not change while the planning is being execute. But in the real world, It is possible to have some unexpected event happen when plan is executing such as machine break during the production plan. Reactive planning is a new idea that allows planner to reactive with the environments.


Planning system in AI is an agent that can develop a strategy to achieve its goal by finding a series of actions that can have a desirable outcome. Planning system uses the reason about actions as an essential component to solve many practical problems.

For example, in most manufacturing, there is a trend to higher capitalization in plant, smaller batch sizes and tighter controls on inventories. All these trends argue for computer control of the manufacturing process which requires reasoning about actions at almost every level, from process routing, to setting up the job shop. In competitive markets with small batch sizes, manufacturers must be able to reconfigure in response to shifts in customer demands for products and to contractual obligations. Mathematical modeling and operations-research techniques, while appropriate for long range predictions, cannot accomplish shorter-term tactical planning when it is important to have a clear understanding of the ...

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...r produces a world model that satisfies the goal. Classical planner assume that the world state is not change during the plan is execute. But Reactive planning allow the world stat to change during the plan


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