We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, M, and given multiple linear-time (ω-regu...
Kousha Etessami, Marta Z. Kwiatkowska, Moshe Y. Va...
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
We have presented an optimal on-chip buffer allocation and buffer insertion methodology which uses stochastic models of the architecture. This methodology uses finite buffer s...
Sankalp Kallakuri, Nattawut Thepayasuwan, Alex Dob...
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...