Deep RL
4,525 papers
Papers per year
1
9
14
15
9
21
27
32
21
17
11
33
103
241
418
498
571
533
585
678
507
181
'5
'10
'15
'20
'25
Papers
Deciding What to Learn: A Rate-Distortion Approach
ICML 2021
Decision Transformer: Reinforcement Learning via Sequence Modeling
NeurIPS 2021
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices
ICML 2021
Decoupling Representation Learning from Reinforcement Learning
ICML 2021
Decoupling Value and Policy for Generalization in Reinforcement Learning
ICML 2021
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks
NeurIPS 2021
Deep Bayesian Quadrature Policy Optimization
AAAI 2021
Deep Coherent Exploration for Continuous Control
ICML 2021
Deep Innovation Protection: Confronting the Credit Assignment Problem in Training Heterogeneous Neural Architectures
AAAI 2021
Deep Radial-Basis Value Functions for Continuous Control
AAAI 2021
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
ICML 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice
NeurIPS 2021
Deep Reinforcement Learning Boosted Partial Domain Adaptation
IJCAI 2021
Deep Reinforcement Learning for a Dictionary Based Compression Schema (Student Abstract)
AAAI 2021
Deep Reinforcement Learning for Multi-contact Motion Planning of Hexapod Robots
IJCAI 2021
Deep Reinforcement Learning for Navigation in AAA Video Games
IJCAI 2021
Deep Residual Reinforcement Learning (Extended Abstract)
IJCAI 2021
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning
AAAI 2021
DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding
AAAI 2021
Density Constrained Reinforcement Learning
ICML 2021
Design of Experiments for Stochastic Contextual Linear Bandits
NeurIPS 2021
Detecting Rewards Deterioration in Episodic Reinforcement Learning
ICML 2021
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
ICML 2021
Discovering and Achieving Goals via World Models
NeurIPS 2021
Discovering symbolic policies with deep reinforcement learning
ICML 2021