CrowdPlanr:利用人群让计划变得更容易

Ilia Lotosh, T. Milo, Slava Novgorodov
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引用次数: 23

摘要

最近的研究表明,众包可以有效地用于解决计算机难以解决的问题,例如光学字符识别和天然蛋白质结构构型的识别[1]。在这个演示中,我们建议使用人群的力量来解决日常生活中经常出现的另一个难题——当目标难以形式化时,计划一系列行动。例如,在假期中计划要参观的地方/景点的顺序,目标是最大限度地享受假期,或者在学术时间表计划中计划课程的顺序,目标是获得给定学科领域的扎实知识。这样的目标对于人类来说可能很容易理解,但对于计算机来说很难甚至不可能形式化。我们提出了一种新的算法来有效地利用人群来帮助解决这类规划问题。该算法逐步构建所需的计划,在每一步中选择最优的“最佳”问题,以便需要提出的问题总数最小化。我们在度假旅行规划系统crowdplanner中展示了我们解决方案的有效性。给定目的地、日期、喜欢的活动和其他限制条件,CrowdPlanr会让人们制定一个假期计划(要去的地方的顺序),以期最大限度地享受假期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CrowdPlanr: Planning made easy with crowd
Recent research has shown that crowd sourcing can be used effectively to solve problems that are difficult for computers, e.g., optical character recognition and identification of the structural configuration of natural proteins [1]. In this demo we propose to use the power of the crowd to address yet another difficult problem that frequently occurs in a daily life-planning a sequence of actions, when the goal is hard to formalize. For example, planning the sequence of places/attractions to visit in the course of a vacation, where the goal is to enjoy the resulting vacation the most, or planning the sequence of courses to take in an academic schedule planning, where the goal is to obtain solid knowledge of a given subject domain. Such goals may be easily understandable by humans, but hard or even impossible to formalize for a computer. We present a novel algorithm for efficiently harnessing the crowd to assist in solving such planning problems. The algorithm builds the desired plans incrementally, optimally choosing at each step the `best' questions so that the overall number of questions that need to be asked is minimized. We demonstrate the effectiveness of our solution in CrowdPlanr, a system for vacation travel planning. Given a destination, dates, preferred activities and other constraints CrowdPlanr employs the crowd to build a vacation plan (sequence of places to visit) that is expected to maximize the “enjoyment” of the vacation.
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