使用高層觀點描述規劃行動方案之研究

A study on planning actions by using high- level description

許金賢(Hsu, Alex)

指導教授 ： 陳穎平

國立交通大學/資訊學院/資訊科學與工程研究所/碩士(2019年)

摘要

隨著科技發展,人們逐漸進入AI時代,透過機器學習,各種工作漸漸地能夠自動化完成,而原本在該工作崗位的人(下稱舊有工作者)將面臨被取代的命運。目前的機器學習多為以使用資料來訓練為主流,但一般人不易取得大量資料,或是還未存在公開資料,並且舊有工作者並非對自動化領域熟悉,難以自行建立自動化機制;或者,當機器學習領域之專家或學者要與舊有工作者合作時,舊有工作者可能會考量到自己未來的工作被取代,使得自動化不易發展,因此,如果有一套方法能夠讓舊有工作者自行建立自動化機制,不失為一種考量。再者,考量到歷來已有多種優化方法藉以尋求最佳解,因此本研究將不著重於尋求最佳解,而是著重在使用者可自行建立自動化代理人。

關鍵字

高層觀點描述 ； 規劃

並列摘要

As the development of technology, people step into AI era. Several tasks can be done automatically. People on his or her jobs are facing replacement. Nowadays, most machine learning mechanisms are data-driven. However, it's hard to obtain a large scale or a non-public dataset for an average person, and he or she may not be familiar with automation mechanism. Thus, having a method to let an average person build an automation mechanism might be a consideration. As there are several optimization techniques, this research will not focus on finding optimal solutions but letting users be able to build an automation mechanism by themselves.

並列關鍵字

high-level description ； planning

參考文獻

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