We consider Markov Decision Processes (MDPs) as transformers on probability distributions, where with respect to a scheduler that resolves nondeterminism, the MDP can be seen as ex...
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul A...
— We consider the general problem of optimizing the performance of OBS networks with multiple traffic classes subject to strict (absolute) QoS constraints in terms of the end-to...
CaVi provides a uniform interface to state-of-the-art simulation methods and formal verification methods for wireless sensor network. Simulation is suitable to examine the behavi...
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...