Now showing items 41-45 of 45
Risk Sensitive Control of Markov Processes in Countable State Space
In this paper we consider infinite horizon risk-sensitive control of Markov processes with discrete time and denumerable state space. This problem is solved proving, under suitable conditions, that there exists a bounded ...
Simulation-Based Algorithms for Average Cost Markov Decision Processes
In this paper, we give a summary of recent development of simulation-based algorithmsfor average cost MDP problems, which are different from those for discounted cost problems or shortest pathproblems. We introduce both ...
A Discrete Event Systems Approach for Protocol Conversion
A Protocol mismatch occurs when heterogeneous networks try to communicate with each other. Such mismatches are inevitable due to the proliferation of a multitude of networking architectures, hardware, and software on one ...
An Adaptive Sampling Algorithm for Solving Markov Decision Processes
Based on recent results for multi-armed bandit problems, we propose an adaptive sampling algorithm that approximates the optimal value of a finite horizon Markov decision process (MDP) with infinite state space but finite ...
Evolutionary Policy Iteration for Solving Markov Decision Processes
We propose a novel algorithm called Evolutionary Policy Iteration (EPI) for solving infinite horizon discounted reward Markov Decision Process (MDP) problems. EPI inherits the spirit of the well-known PI algorithm but ...