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← Reinforcement Learning
Reinforcement Learning ›

Methods

6,493 papers (10 classified directly here)

Subtopics

Deep RL (3,886) Policy Learning (2,076) Multi-Agent Systems (1,019) Offline RL (726) Meta-Learning (25) Model-Based RL (12)

Papers per year

2
31
34
727
530
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Papers (including subtopics)

POLITEX: Regret Bounds for Policy Iteration using Expert Prediction ICML 2019
Batch Policy Learning under Constraints ICML 2019
Target-Based Temporal-Difference Learning ICML 2019
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes ICML 2019
Taming MAML: Efficient unbiased meta-reinforcement learning ICML 2019
Guided evolutionary strategies: augmenting random search with surrogate gradients ICML 2019
Calibrated Model-Based Deep Reinforcement Learning ICML 2019
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs ICML 2019
Distributional Reinforcement Learning for Efficient Exploration ICML 2019
Reinforcement Learning in Configurable Continuous Environments ICML 2019
Remember and Forget for Experience Replay ICML 2019
Optimistic Policy Optimization via Multiple Importance Sampling ICML 2019
Fingerprint Policy Optimisation for Robust Reinforcement Learning ICML 2019
Nonlinear Distributional Gradient Temporal-Difference Learning ICML 2019
Learning to Collaborate in Markov Decision Processes ICML 2019
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables ICML 2019
Statistics and Samples in Distributional Reinforcement Learning ICML 2019
Exploration Conscious Reinforcement Learning Revisited ICML 2019
Hessian Aided Policy Gradient ICML 2019
Model-Based Active Exploration ICML 2019
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning ICML 2019
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective ICML 2019
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning ICML 2019
Provably Efficient Imitation Learning from Observation Alone ICML 2019
Making Deep Q-learning methods robust to time discretization ICML 2019