Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
Human learning in Atari
Natural Gradient Deep Q-learning
Rainbow: Combining Improvements in Deep Reinforcement Learning
Learning to predict where to look in interactive environments using deep recurrent q-learning
Quasi-Newton Optimization in Deep Q-Learning for Playing ATARI Games
Deep Reinforcement Learning with Double Q-learning
Deep reinforcement learning with experience replay based on SARSA
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Learning from Demonstrations: Is It Worth Estimating a Reward Function?
Deep Q-learning from Demonstrations
A4C: Anticipatory Asynchronous Advantage Actor-Critic
Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games
A Neuroevolution Approach to General Atari Game Playing
Continuous Deep Q-Learning with Model-based Acceleration
Evolving Neural Network Agents in the NERO Video Game
Monte Carlo Q-learning for General Game Playing
A Comparison of learning algorithms on the Arcade Learning Environment
Active Reinforcement Learning : Observing Rewards at a Cost
On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning
Interference of Khat with Treatment of Paranoid Schizophrenia
Network Coding for Distributed Storage Systems
Domain-Independent Optimistic Initialization for Reinforcement Learning
strategic decision support using computerised morphological analysis .
Towards fifth-generation (5G) optical transport networks