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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Bounded non-deterministic planning for multimedia adaptation
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Bounded non-deterministic planning for multimedia adaptation

机译：多媒体适配的有界不确定性规划

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摘要

This paper proposes a novel combination of artificial intelligence planning and other techniques for improving decision-making in the context of multi-step multimedia content adaptation. In particular, it describes a method that allows decision-making (selecting the adaptation to perform) in situations where third-party pluggable multimedia conversion modules are involved and the multimedia adaptation planner does not know their exact adaptation capabilities. In this approach, the multimedia adaptation planner module is only responsible for a part of the required decisions; the pluggable modules make additional decisions based on different criteria. We demonstrate that partial decision-making is not only attainable, but also introduces advantages with respect to a system in which these conversion modules are not capable of providing additional decisions. This means that transferring decisions from the multi-step multimedia adaptation planner to the pluggable conversion modules increases the flexibility of the adaptation. Moreover, by allowing conversion modules to be only partially described, the range of problems that these modules can address increases, while significantly decreasing both the description length of the adaptation capabilities and the planning decision time. Finally, we specify the conditions under which knowing the partial adaptation capabilities of a set of conversion modules will be enough to compute a proper adaptation plan.
机译：本文提出了一种人工智能计划与其他技术的新颖组合，以在多步骤多媒体内容自适应的情况下改善决策。特别地，它描述了一种方法，该方法允许在涉及第三方可插拔多媒体转换模块并且多媒体自适应计划者不知道其确切自适应能力的情况下进行决策（选择要执行的自适应）。在这种方法中，多媒体适应计划器模块仅负责部分必需的决策。可插拔模块根据不同标准做出其他决策。我们证明，不仅可以实现部分决策，而且相对于其中这些转换模块无法提供其他决策的系统而言，它还引入了优势。这意味着将决策从多步骤多媒体适配计划器传输到可插拔转换模块会增加适配的灵活性。此外，通过仅部分地描述转换模块，增加了这些模块可以解决的问题范围，同时显着减小了自适应能力的描述长度和规划决策时间。最后，我们指定条件，在此条件下，一组转换模块的部分适应能力将足以计算适当的适应计划。

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