ID 原文 译文
56438 在任何时刻, 一个玩家探索活动的结果是一个关于当前拼图问题的片段解, 以及一组被该玩家判断为错误的图块邻接关系.在融合活动中, 拼图环境实时地将所有玩家的当前探索结果融合在一起, 形成一个不断演化的群体观点图.在反馈活动中, 对于每一个玩家, 拼图环境根据该玩家的当前探索结果和当前的群体观点图, 向该玩家推荐特定的信息, 以加速其拼图进程.我们实现了一个支持上述方法的多人在线拼图环境, 并在 2∼10 人规模的玩家群体中进行了初步的实验. Through the feedback activity, each player is provided with personalized feedback information based on thecurrent COG and the player’s current exploration results, in order to accelerate his/her puzzle-solving process.
56439 实验结果表明: Exploratory experiments show that:
56440 (1) 在这一多人拼图环境中, 拼图求解时间大致正比于玩家数量的倒数, 且以玩家群体中的最强个体为基准点, 群体拼图效率能够实现 31. 36%∼64. 57% 的提升; (1) Supported by this approach, the time to solve PJ puzzles is nearly linear withrespect to the reciprocal of the number of players. Furthermore, compared with the best single players in the ex?periments, the puzzle-solving time decreases by 31. 36%–64. 57% on average for groups composed of 2 to 10 players.
56441 (2) 在该环境中, 最快完成拼图的玩家获得的反馈信息平均具有 86. 34% 的准确率, 且随着群体规模的增加, 反馈信息在最快玩家拼图结果中的平均占比逐渐从 20% 增加到 45% 左右; (2) Supported by this approach, the feedback information received by the best player in a group has an averageprecision of 86. 34%, and, as the group size increases, the feedback information in the puzzle-solving result of thebest player increases gradually from 20% to 45%.
56442 (3) 相比于面对面协同的群体拼图求解方式, 该环境展示出更好的群体规模可扩展性, 且拼图结果总是具有 100% 的正确率, 而拼图问题自动求解算法平均只具有 52% 的正确率. (3) This approach exhibits a better scalability with puzzle sizethan that of a face-to-face collaboration among ten players. Additionally, it always leads to 100%-accurate puzzle?solving results, whereas the results of the automated PJ-puzzle solver have an average accuracy of only 52%.
56443 我们希望本文工作能够为探索群体智能在互联网环境下的更广泛应用提供一些有用的信息或观点. Itis envisaged that these results will provide useful information or opinions to facilitate a broader application ofhuman collective intelligence in the Internet environment.
56444 本文面向多种硬件平台提出了一套Web3D实时动态光影的协同式渲染系统,该系统把Web前端的硬件性能作为整个云渲染系统中光影渲染任务分配的关键因素.对于Web前端性能较强的硬件设备,系统分配复杂度较高的光影渲染任务给前端,相应的云后端的渲染负担则有所降低; In this work, a Web3D collaborative cloud rendering system for lighting and shadow is proposed,which distributes rendering tasks based on the hardware power of the Web front-end. If the web front-endhardware device has a strong power, the system will allocate more complex rendering tasks to it, and the cloudback-end rendering tasks will be reduced accordingly.
56445 反之,系统则分配复杂度较低的光影渲染任务给前端,相应的云后端承担大部分的渲染任务. Conversely, if the front-hand hardware has limited power,its rendering tasks will decrease, whereas the rendering tasks allocated to the cloud back-end will increase.
56446 在上述机制的引导下,该系统的前后端部署了4类关键的实时光影渲染算法,最终通过对算法运行帧率、算法所在设备的运行效率以及光影渲染结果等多种数据的分析,验证了部署的合理性. Basedon the above strategy, four key real-time lighting-and-shadow rendering algorithms were simultaneously deployedat the front-and-back ends of the system. Finally, the rationality of the deployment was verified by analyzingvarious data, such as the frame rate of the algorithm, the hardware use efficiency, and the performance of lightingand shadow rendering.
56447 衡量航母作战性能的重要指标是舰载机出动架次率,而影响舰载机出动架次率的关键因素是舰载机保障作业调度效率. The carrier-borne aircraft dispatch rate is an important indicator to measure the combat performanceof an aircraft carrier. The key factor affecting the carrier-borne aircraft dispatch rate is the efficiency of thecarrier aircraft support operation scheduling.