We introduce a journey planning problem in multi-modal transportation networks under uncertainty. The goal is to find a journey, possibly involving transfers between different transport services, from a given origin to a given destination within a specified time horizon. Due to uncertainty in...

In this paper we develop the convex analytic approach to a discounted discrete-time Markov decision process (DTMDP) in Borel state and action spaces with N constraints. Unlike the classic discounted models, we allow a non-constant discount factor. After defining and characterizing the...

A Markov decision process (MDP) is a general model for solving planning problems under uncertainty. It has been extended to multiobjective MDP to address multicriteria or multiagent problems in which the value of a decision must be evaluated according to several viewpoints, sometimes...