WW11: USING MARKOV DECISION MODELS TO DEVELOP OPTIMAL TREATMENT PATHWAYS: AN ILLUSTRATION

Reconnguring Distributed Systems Using Markov-decision Models

When reconnguring distributed systems, either because failures and/or repairs have occurred, or because the workload requirements have changed over time, an alternative connguration has to be selected, thereby taking performability and costs, i.e., quality of service, requirements into consideration. In this paper we will present the use of Markov-decision models to decide upon such reconngurat...

An Illustration of the Use of Markov Decision Processes to Represent Student Growth (Learning)

Over the course of instruction, instructors generally collect a great deal of information about each student. Integrating that information intelligently requires models for how a student’s proficiency changes over time. Armed with such models, instructors can filter the data—more accurately estimate the student’s current proficiency levels—and forecast the student’s future proficiency levels. T...

Modeling Medical Treatment Using Markov Decision Processes

Ordinal Decision Models for Markov Decision Processes

Setting the values of rewards in Markov decision processes (MDP) may be a difficult task. In this paper, we consider two ordinal decision models for MDPs where only an order is known over rewards. The first one, which has been proposed recently in MDPs [23], defines preferences with respect to a reference point. The second model, which can been viewed as the dual approach of the first one, is b...

Using rxncon to develop rule based models

We present a protocol for building, validating and simulating models of signal transduction networks. These networks are challenging modelling targets due to the combinatorial complexity and sparse data, which have made it a major challenge even to formalise the current knowledge. To address this, the community has developed methods to model biomolecular reaction networks based on site dynamics...