Bridge maintenance and replacement optimization methods use deterioration models to predict the future condition of bridge components. The purpose of this paper is to develop a framework for bridge maintenance optimization using a deterioration model that takes into account aspects of the history of the bridge condition and maintenance, while allowing the use of efficient optimization technique...

Pavement deterioration rate is very difficult to predict because of the complexities in determining the pavement condition rating or difficulty in collecting detailed data, particularly in absence of sophisticated equipment or trained staff etc. A wide variety of Pavement Maintenance Systems (PMS) are used, but unfortunately either these systems do not use a formalized procedure to determine th...

Robotic applications are characterized by highly dynamic domains, where the agent has neither full control of the environment nor full observability. In those cases a Markovian model of the domain, able to capture all the aspects that the agent might need to predict, is generally not available or excessively complex. Moreover, robots pose relevant constraints on the amount of experience they ca...

In Markov Decision Processes (MDPs), the reward obtained in a state is Markovian, i.e., depends on the last state and action. This dependency makes it difficult to reward more interesting long-term behaviors, such as always closing a door after it has been opened, or providing coffee only following a request. Extending MDPs to handle non-Markovian reward functions was the subject of two previou...

The stochastic reaction diffusion systems may suffer sudden shocks‎, ‎in order to explain this phenomena‎, ‎we use Markovian jumps to model stochastic reaction diffusion systems‎. ‎In this paper‎, ‎we are interested in almost sure exponential stability of stochastic reaction diffusion systems with Markovian jumps‎. ‎Under some reasonable conditions‎, ‎we show that the trivial solution of stocha...