Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Part-Activated Deep Reinforcement Learning for Action Prediction
A Hierarchical Representation for Future Action Prediction
Regret Minimization for Partially Observable Deep Reinforcement Learning
Kickstarting Deep Reinforcement Learning
Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making
Intra-Option Learning about Temporally Abstract Actions
On Improving Deep Reinforcement Learning for POMDPs
Combining deep reinforcement learning with prior knowledge and reasoning
Extracting Action Sequences from Texts Based on Deep Reinforcement Learning
Integrating State Representation Learning Into Deep Reinforcement Learning
Differential Recurrent Neural Networks for Action Recognition
Learning locomotion skills using DeepRL: does the choice of action space matter?
Model-based hierarchical reinforcement learning and human action control
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space
Efficient Parallel Methods for Deep Reinforcement Learning
Exploration-Exploitation Trade-off in Deep Reinforcement Learning
learning to act by predicting the future .
Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching
Model-Free reinforcement learning with continuous action in practice
Unsupervised Predictive Memory in a Goal-Directed Agent
A Novel Measure for Coherence in Statistical Topic Models
Large Margin Methods for Structured and Interdependent Output Variables
Extracting Knowledge for Cultural Heritage Knowledge Base Population
Incremental Learning From Stream Data
Recipes for the linear analysis of EEG