In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
In this paper, we give the rst constant-factor approximationalgorithmfor the rooted Orienteering problem, as well as a new problem that we call the Discounted-Reward TSP, motivate...
Avrim Blum, Shuchi Chawla, David R. Karger, Terran...