With the aim of tracking the deteriorating process of a specific individual multi-state system consisting of more than one multi-state component, a dynamic reliability assessment method which can utilize systemlevel observation history to dynamically update the reliability function of multi-state degraded systems is developed in this paper. The current and future state probabilities of componen...

The redundancy allocation is one of the most important and useful problems in system optimization, especially in electrical and mechanical systems. The object of this problem is to maximize system reliability or availability within a minimum operation cost. Many works have been proposed in this area so far to draw the problem near to real-world situations. While in classic models the system com...

In this paper, we study different methods of solving joint redundancy-availability optimization for series-parallel systems with multi-state components. We analyzed various effective factors on system availability in order to determine the optimum number and version of components in each sub-system and consider the effects of improving failure rates of each component in each sub-system and impr...

The problem of reliability of new object of distributed hardware software (DHS) multi-agent system (MAS) is considered. DHS MAS is determined as a system that is based on agent technologies and consists of both agents and hardware components required for execution of agents and for interaction of agents with an environment. Reliability improvement, fault-recovery and several reliability assessm...

Multi agent Markov decision processes (MMDPs), as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for Multi agent Reinforcement Learning. In this paper, a generalized learning automata based algorithm for finding optimal policies in MMDP is proposed. In the proposed algorithm, MMDP ...