In this paper, we extend the classical result by Huang, Kintala, Kolettis and Fulton (1995), and in addition propose a modified stochastic model to determine the software rejuvena...
Since the early 1970's a number of models have been proposed for estimating software reliability. However, the realism of many of the underlying assumptions and the applicabi...
Decentralized Markov Decision Processes are a powerful general model of decentralized, cooperative multi-agent problem solving. The high complexity of the general problem leads to...
We address the problem of coordinating the plans and schedules for a team of agents in an uncertain and dynamic environment. Bounded rationality, bounded communication, subjectivi...
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...