Partially observable Markov decision processes (POMDPs) have been
successfully applied to various robot motion planning tasks under uncertainty.
However, most existing POMDP algo...
Haoyu Bai, David Hsu, Wee Sun Lee, and Vien A. Ngo
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
Unlike mono-agent systems, multi-agent planing addresses the problem of resolving conflicts between individual and group interests. In this paper, we are using a Decentralized Ve...
The success of probabilistic model checking for discrete-time Markov decision processes and continuous-time Markov chains has led to rich academic and industrial applications. The ...
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...