Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Medical information systems and standards are increasingly based on principled models of at least three distinct sorts of information – patient data, concepts (terminology), and ...
Alan L. Rector, Peter D. Johnson, Samson W. Tu, Ch...
Abstract. We discuss a case study for the hospital scenario where workflow model components are distributed across various computers or devices (e.g. mobile phones, PDAs, sensors, ...
Executing critical systems often rely on humans to make important and sometimes life-critical decisions. As such systems become more complex, the potential for human error to lead...
Lori A. Clarke, Leon J. Osterweil, George S. Avrun...
Markov Decision Processes (MDPs) have been extensively studied and used in the context of planning and decision-making, and many methods exist to find the optimal policy for probl...