Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: The Predictron: End-To-End Learning and Planning
Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning
Predictive representations can link model-based reinforcement learning to model-free mechanisms
Pre-training Neural Networks with Human Demonstrations for Deep Reinforcement Learning
An Actor-Critic Algorithm for Sequence Prediction
M ULTI-TASK LEARNING WITH DEEP MODEL BASED REINFORCEMENT LEARNING
A POMDP formulation of Proactive Learning
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
Approximate Planning in Large POMDPs via Reusable Trajectories
Pretraining Deep Actor-Critic Reinforcement Learning Algorithms With Expert Demonstrations
Learning Abstract Planning Domains and Mappings to Real World Perceptions
Plan explicability and predictability for robot task planning
Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching
Human-like generalization in a machine through predicate learning
Multi-step Linear Dyna-style Planning
Compositional Imitation Learning: Explaining and executing one task at a time
Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Between MDPs and Semi-MDPs: Learning, Planning, and Representing Knowledge at Multiple Temporal Scales
Playing Atari with Deep Reinforcement Learning
Motion Capture and Retargeting of Fish by Monocular Camera
OPTIMIZATION OF HELICAL ANTENNAS
Specified data for tonsil surgery in Germany
Gender Differences in Static and Dynamic Postural Stability Parameters in Community Dwelling Healthy Older Adults