We present two new algorithms for finding optimal strategies for discounted, infinite-horizon, Deterministic Markov Decision Processes (DMDP). The first one is an adaptation of...
Temporal logic is two-valued: formulas are interpreted as either true or false. When applied to the analysis of stochastic systems, or systems with imprecise formal models, tempor...
Luca de Alfaro, Marco Faella, Thomas A. Henzinger,...
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...
Formal analysis of decentralized decision making has become a thriving research area in recent years, producing a number of multi-agent extensions of Markov decision processes. Wh...
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...