Policy Networks with Two-Stage Training for Dialogue Systems

INTRODUCTION. Deep convolutional neural networks (CNNs) have achieved state-of-the-art performance in image classification, object detection and many other ...







Multi-Agents Reinforcement Learning In Iterative Voting
In our simulations we create an iterative voting game with num quest is the number of questions in the election, num agents is the number of voting agents.
Deep Reinforcement Learning for Dynamical Systems
It works by taking the principle of TD prediction and applying it in order to learn a Q-function Q(st,at), instead of a V-function V(st). It is ...
Action Elimination with Deep Reinforcement Learning - NIPS
The optimal time that it takes to solve each quest is 6 in-game timesteps for the Egg quest, 11 for the Troll quest and 350 for ?Open Zork?. The agent's goal in ...



Autres Cours:

Deep Reinforcement Learning for Dynamical Systems - Webthesis