We present a heuristic search algorithm for solving first-order Markov Decision Processes (FOMDPs). Our approach combines first-order state abstraction that avoids evaluating stat...
ion in PRISM1 Mark Kattenbelt Marta Kwiatkowska Gethin Norman David Parker Oxford University Computing Laboratory, Oxford, UK Modelling and verification of systems such as communi...
Mark Kattenbelt, Marta Z. Kwiatkowska, Gethin Norm...
Progressive processing allows a system to satisfy a set of requests under time pressure by limiting the amount of processing allocated to each task based on a predefined hierarchic...
- We present a novel hierarchical modular decision engine for lung nodule detection from CT images implemented by Artificial Neural Networks. The proposed Computer Aided Detection ...
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...