Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Subgoal Discovery for Hierarchical Dialogue Policy Learning
Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning
Scaling up POMDPs for Dialog Management: The ``Summary POMDP'' Method
Learning Robust Dialog Policies in Noisy Environments
On-line Dialogue Policy Learning with Companion Teaching.
Iterative policy learning in end-to-end trainable task-oriented neural dialog models
Micro-Objective Learning : Accelerating Deep Reinforcement Learning through the Discovery of Continuous Subgoals
Scaling up deep reinforcement learning for multi-domain dialogue systems
Deep Reinforcement Learning for Dialogue Generation
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
Learning End-to-End Goal-Oriented Dialog with Multiple Answers
Policy Learning for Domain Selection in an Extensible Multi-domain Spoken Dialogue System
Multi-domain dialogue success classifiers for policy training
Strategy and Policy Learning for Non-Task-Oriented Conversational Systems
Interactive reinforcement learning for task-oriented dialogue management
On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems
End-to-end optimization of goal-driven and visually grounded dialogue systems
Reinforcement Learning for Dialog Management using Least-Squares Policy Iteration and Fast Feature Selection
An Integrated Neural Network Model for Domain Action Determination in Goal-Oriented Dialogues
Distributed dialogue policies for multi-domain statistical dialogue management
Sample-efficient Actor-Critic Reinforcement Learning with Supervised Data for Dialogue Management
A Multi-Armed Bandit Approach for Online Expert Selection in Markov Decision Processes
Cosine Similarity Scoring without Score Normalization Techniques
The growth of human scalp hair mediated by visible red light laser and LED sources in males
Integration of ICT in Education: Key Challenges
Intra-Option Learning about Temporally Abstract Actions