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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)

GMAC: A Distributional Perspective on Actor-Critic Framework ICML 2021
Emergent Social Learning via Multi-agent Reinforcement Learning ICML 2021
Continuous Coordination As a Realistic Scenario for Lifelong Learning ICML 2021
Policy Caches with Successor Features ICML 2021
Interactive Learning from Activity Description ICML 2021
Temporal Predictive Coding For Model-Based Planning In Latent Space ICML 2021
Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods ICML 2021
Vector Quantized Models for Planning ICML 2021
Ensemble Bootstrapping for Q-Learning ICML 2021
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization ICML 2021
Density Constrained Reinforcement Learning ICML 2021
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions ICML 2021
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game ICML 2021
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning ICML 2021
Decoupling Value and Policy for Generalization in Reinforcement Learning ICML 2021
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL ICML 2021
Model-Based Reinforcement Learning via Latent-Space Collocation ICML 2021
Recomposing the Reinforcement Learning Building Blocks with Hypernetworks ICML 2021
State Entropy Maximization with Random Encoders for Efficient Exploration ICML 2021
State Relevance for Off-Policy Evaluation ICML 2021
Structured World Belief for Reinforcement Learning in POMDP ICML 2021
Multi-Task Reinforcement Learning with Context-based Representations ICML 2021
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks ICML 2021
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration ICML 2021
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning ICML 2021