The problem of point-to-point shortest path computation in spatial networks is extensively studied with many approaches proposed to speed-up the computation. Most of the existing ...
Ugur Demiryurek, Farnoush Banaei Kashani, Cyrus Sh...
This paper considers algorithms and complexity results for the generation of counterexamples in model checking of probabilistic until-formulae in discrete-time Markov chains (DTMCs...
: The path planning problem is relevant for all applications in which a mobil robot should autonomously navigate. Finding the shortest path in an environment that is only partialy ...
Ulrich Roth, Marc Walker, Arne Hilmann, Heinrich K...
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...
In this paper, we survey algorithms for shortest paths in dynamic networks. Although research on this problem spans over more than three decades, in the last couple of years many ...