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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)

Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability ICML 2017
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? ICML 2017
Count-Based Exploration with Neural Density Models ICML 2017
Curiosity-driven Exploration by Self-supervised Prediction ICML 2017
Robust Adversarial Reinforcement Learning ICML 2017
Neural Episodic Control ICML 2017
Hierarchy Through Composition with Multitask LMDPs ICML 2017
World of Bits: An Open-Domain Platform for Web-Based Agents ICML 2017
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction ICML 2017
Model-Independent Online Learning for Influence Maximization ICML 2017
FeUdal Networks for Hierarchical Reinforcement Learning ICML 2017
Latent Intention Dialogue Models ICML 2017
Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits IJCAI 2017
Multi-Agent Planning with Baseline Regret Minimization IJCAI 2017
Transfer Learning in Multi-Armed Bandits: A Causal Approach IJCAI 2017
Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions IJCAI 2017
Sample Efficient Policy Search for Optimal Stopping Domains IJCAI 2017
Learning Sparse Representations in Reinforcement Learning with Sparse Coding IJCAI 2017
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming IJCAI 2017
Count-Based Exploration in Feature Space for Reinforcement Learning IJCAI 2017
End-to-end optimization of goal-driven and visually grounded dialogue systems IJCAI 2017
Improving Reinforcement Learning with Confidence-Based Demonstrations IJCAI 2017
Sequence Prediction with Unlabeled Data by Reward Function Learning IJCAI 2017
Multi-Task Deep Reinforcement Learning for Continuous Action Control IJCAI 2017
Weighted Double Q-learning IJCAI 2017