Methods
8,258 papers (12 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Papers per year
6
1
2
2
16
21
24
16
31
36
44
47
44
37
63
171
350
606
801
920
974
1,144
1,380
1,203
319
'5
'10
'15
'20
'25
Papers (including subtopics)
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
ICML 2021
The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies
L4DC 2021
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
NeurIPS 2021
The Difficulty of Passive Learning in Deep Reinforcement Learning
NeurIPS 2021
The Emergence of Individuality
ICML 2021
The Logical Options Framework
ICML 2021
Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation
AAAI 2021
The Sample Complexity of Teaching by Reinforcement on Q-Learning
AAAI 2021
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning
NeurIPS 2021
The Successful Ingredients of Policy Gradient Algorithms
IJCAI 2021
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning
AAAI 2021
Thompson sampling for Markov games with piecewise stationary opponent policies
UAI 2021
ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning
CoRL 2021
Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning
ACML 2021
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods
NeurIPS 2021
TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting
EMNLP 2021
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach
EMNLP 2021
Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
ICML 2021
Towards Deeper Deep Reinforcement Learning with Spectral Normalization
NeurIPS 2021
Towards Distraction-Robust Active Visual Tracking
ICML 2021
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning
AAAI 2021
Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning
NeurIPS 2021
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism
NeurIPS 2021
Towards mental time travel: a hierarchical memory for reinforcement learning agents
NeurIPS 2021
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
ICML 2021