Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
This paper describes a deterministic approach to adaptive state and parameter estimation using a multiple model structure. In the set-up adopted, the plant of interest is described...
The main purpose of event-based control, if compared to periodic control, is to minimize data transfer or processing power in networked control systems. Current methods have an (i...
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 ...
Curriculum based on internetworking devices is primarily based on the Command Line Interface (CLI) and case studies. However a single CLI command may produce output that is not on...