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The Cartographer
Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs
January 03, 2017 Β· Declared Dead Β· π International Workshop on Multi-disciplinary Trends in Artificial Intelligence
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Authors
Dajian Li, Paul Weng, Orkun Karabasoglu
arXiv ID
1701.00642
Category
cs.AI: Artificial Intelligence
Citations
4
Venue
International Workshop on Multi-disciplinary Trends in Artificial Intelligence
Last Checked
4 months ago
Abstract
In this paper, we tackle the problem of risk-averse route planning in a transportation network with time-dependent and stochastic costs. To solve this problem, we propose an adaptation of the A* algorithm that accommodates any risk measure or decision criterion that is monotonic with first-order stochastic dominance. We also present a case study of our algorithm on the Manhattan, NYC, transportation network.
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