We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
When using a planner-based agent architecture, many things can go wrong. First and foremost, an agent might fail to execute one of the planned actions for some reasons. Even more ...
Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...
We do not interact with systems without first performing some physical action on a physical device. This paper shows how formal notations and formal models can be developed to acc...
Alan J. Dix, Masitah Ghazali, Devina Ramduny-Ellis
A direct adaptive neural network control system with and without integral action term is designed for the general class of continuous biological fermentation processes. The control...
Ieroham S. Baruch, Petia Georgieva, Josefina Barre...