从等视域波动来识别可理解性的跳跃——通过点连接绘制潜在的惊喜时刻位置

Detection of Intelligibility Leaps Using Isovist-Waves:Joining the Dots to Map Potential ’Aha Moment’ Locations

论文描述了一种新计算方法的探索和进展,该方法在学习新的空间配置过程中检测潜在的惊喜时刻的位置。惊喜时刻是指突然重新定向的实例,其中对空间配置的整体理解突然(经常出乎意料)增加。我们开发了一种新的计算方法来检测这种现象,通过从可导航空间内的初始随机点产生可视,然后从最新迭代的遮挡边缘迭代地产生新的可视点。当新的可视能够与以前生成的可视重新连接时,这种连接被认为是特别有利的(对于导航器),并且新链接的属性(例如位置)会被记录下来。通过该方法,空间配置被逐步“探索”,同时可以检测全局配置的集成性以及可理解性变化。我们展示了3个案例研究:希利尔(Hillier)的清晰世界/城镇、凡德罗(Van der Rohe)的巴塞罗那馆和赫茨伯格(Hertzberger)的贝尔中央办公综合楼。结果表明,基于可视信息下“播种”出来的潜在惊喜位置是系统性的,并且出现在大型空间单元和信息单元之间的交叉点。因此,我们假设该度量与其他现有的空间句法概念(聚类系数、e-和s-空间、揭示性)具有相似性,但在关注与先前看到位置的成对连接方面也显得不同。我们假设上述的测量方式对人们在空间探索或学习过程中识别捷径的位置较为敏感。论文最后讨论了未来的研究方向。

Our paper describes the exploration of and progress towards a new computational method to detect the location of potential’aha moments’during the learning of a novel spatial configuration.’Aha moments’refer to instances of sudden reorientation where the overall understanding of spatial configuration suddenly,and often unexpectedly,increases.We developed a novel computational approach to detect such a phenomenon,by spawning isovists from initial random points within the navigable space,then iteratively seeding new isovist points from the occluding edges of the latest iteration.When new isovists are able to reconnect with previously generated ones,the connection is held to be particularly advantageous(to a navigator)and the new link’s attributes,such as location,are noted.With our method,the spatial configuration is’explored’progressively,simultaneously allowing the detection of changes in integration and intelligibility of the configuration as a whole.We present the outcomes of applying our method to three case-studies;Hillier’s legible world/town,van der Rohe’s Barcelona Pavilion,and Hertzberger’s Beheer Centraal Offices.The results show that isovist-derived,potential’aha locations’are systematic,and appear at the intersections between large spatial and informational units.As such,the measure is assumed to have similarities with other,existing space syntax concepts(clustering coefficients,e-and s-spaces,revelation)but is also appears distinct in its focus on pairwise-connections with previously seen locations.We hypothesise that our measure is highly sensitive to locations where people identify shortcuts during spatial exploration or learning.The paper concludes with a discussion of future research directions.