—Cooperative communication has attracted dramatic attention in the last few years due to its advantage in mitigating channel fading. Despite much effort that has been made in the...
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
A stochastic graph game is played by two players on a game graph with probabilistic transitions. We consider stochastic graph games with -regular winning conditions specified as Ra...
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...
A long-lived agent continually faces new tasks in its environment. Such an agent may be able to use knowledge learned in solving earlier tasks to produce candidate policies for it...