85 citations · 231 across the 11 of their papers we have counts for
3 papers · 1 filter
Deep Reinforcement Learning for Multi-Domain Dialogue Systems
Heriberto Cuayáhuitl, Seunghak Yu, Ashley Williamson +1
Standard deep reinforcement learning methods such as Deep Q-Networks (DQN) for multiple tasks (domains) face scalability problems. We propose a method for multi-domain dialogue pol…
Training an Interactive Humanoid Robot Using Multimodal Deep Reinforcement Learning
Heriberto Cuayáhuitl, Guillaume Couly, Clément Olalainty
Training robots to perceive, act and communicate using multiple modalities still represents a challenging problem, particularly if robots are expected to learn efficiently from sma…
SimpleDS: A Simple Deep Reinforcement Learning Dialogue System
Heriberto Cuayáhuitl
This paper presents 'SimpleDS', a simple and publicly available dialogue system trained with deep reinforcement learning. In contrast to previous reinforcement learning dialogue sy…