Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
In multiple criteria Markov Decision Processes (MDP) where multiple costs are incurred at every decision point, current methods solve them by minimising the expected primary cost ...
Being part of a larger research program, this paper focuses on the impacts of so-called 'Digital Video Recorders' (DVRs) on the video content services industry. First, i...
: Testing of a software application serves the accomplishment of two dis tinct objectives: ensuring functionality and end-user acceptance. However, with an increasing desire for mo...
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...