物理和概念系统中的容错但特殊的寻路
Fault-Tolerant, but Paradoxical Path-Finding in Physical and Conceptual Systems
摘要：
我们报告我们的初步调查的可靠性和路径查找为基础的模型，并提出未来感兴趣的领域。受校园建设项目中破损的人行道的启发，我们开发了两个模型来导航这个“不可靠的网络”。这些都是基于从目的地向后的“累积风险”的概念，并且都在有向非循环图上操作，每个边缘都有失败的概率。第一个用来介绍第二个更保守的模型，并解决了第二个模型的缺陷。接下来，我们展示了一个悖论，当这些模型被用来构建多项式的概念网络，如设计过程和软件开发生存周期。当网络的风险均匀增加时，最可靠的路径从更宽更长变为更短更窄。如果我们让专业人员缺乏经验--比如入门级厨师和软件开发人员--代表边缘失败的概率，这种路径上的变化是否意味着新手应该用更少的“备份”计划来遵循指令，而那些有替代路线的人应该由专家来遵循？
英文摘要：
We report our initial investigations into reliability and path-finding based models and propose future areas of interest. Inspired by broken sidewalks during on-campus construction projects, we develop two models for navigating this "unreliable network." These are based on a concept of "accumulating risk" backward from the destination, and both operate on directed acyclic graphs with a probability of failure associated with each edge. The first serves to introduce and has faults addressed by the second, more conservative model. Next, we show a paradox when these models are used to construct polynomials on conceptual networks, such as design processes and software development life cycles. When the risk of a network increases uniformly, the most reliable path changes from wider and longer to shorter and narrower. If we let professional inexperience--such as with entry level cooks and software developers--represent probability of edge failure, does this change in path imply that the novice should follow instructions with fewer "back-up" plans, yet those with alternative routes should be followed by the expert?
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
