Fault-Tolerant, but Paradoxical Path-Finding in Physical and Conceptual Systems
This addresses reliability issues in physical and conceptual systems, but it appears incremental as it builds on existing path-finding models with new insights into paradoxical behavior.
The paper tackles the problem of path-finding in unreliable networks, such as broken sidewalks or conceptual systems, by developing two models based on accumulating risk from the destination, and reveals a paradox where increased uniform risk shifts the most reliable path from wider and longer to shorter and narrower.
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?