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Preference-based planning : ウィキペディア英語版
Preference-based planning
In artificial intelligence, preference-based planning is a form of automated planning and scheduling which focuses on producing plans that additionally satisfy as many user-specified preferences as possible. In many problem domains, a task can be accomplished by various sequences of actions (also known as plans). These plans can vary in quality: there can be many ways to solve a problem but one generally prefers a way that is, e.g., cost-effective, quick and safe.
Preference-based planners take these preferences into account when producing a plan for a given problem. Examples of preference-based planning software include ''PPLAN''〔(PPLAN ), Bienvenu et al.〕 and ''HTNPlan-P''〔(HTN Planning with Preferences ), Sohrabi et al.〕 (preference-based HTN planning).
== Overview ==

Preferences can be regarded as soft constraints on a plan. The quality of a plan increases when more preferences are satisfied but it may not be possible to satisfy all preferences in a single plan. This differs from hard constraints which must be satisfied in all plans produced by the planning software. These hard constraints are part of the domain knowledge while the soft constraints (or preferences) are separately specified by the user. This allows the same domain knowledge to be reused for various users who may have different preferences.
The use of preferences may also increase the length of a plan in order to satisfy more preferences. For example, when planning a journey from home to school, the user may prefer to buy a cup of coffee along the way. The planning software could now plan to visit Starbucks first and then continue to school.〔(Planning with Preferences using Logic Programming ), Son and Pontelli〕 This increases the length of the plan but the user's preference is satisfied.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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