Abstract. We consider the problem of finding shortest paths in a graph with independent randomly distributed edge lengths. Our goal is to maximize the probability that the path len...
Evdokia Nikolova, Jonathan A. Kelner, Matthew Bran...
We obtain the first approximation algorithm for finding the k-simple shortest paths connecting a pair of vertices in a weighted directed graph. Our algorithm is deterministic an...
We consider the problem of computing shortest paths in three-dimensions in the presence of a single-obstacle polyhedral terrain, and present a new algorithm that for any p 1, comp...
Given a planar graph on n nodes with costs weights on its edges, de ne the distance between nodes i and j as the length of the shortest path between i and j. Consider this as an i...
Sanjeev Arora, Michelangelo Grigni, David R. Karge...
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...