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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)

Runtime Neural Pruning NIPS 2017
Boltzmann Exploration Done Right NIPS 2017
Policy Gradient With Value Function Approximation For Collective Multiagent Planning NIPS 2017
Dynamic-Depth Context Tree Weighting NIPS 2017
Deep Reinforcement Learning from Human Preferences NIPS 2017
Learning Combinatorial Optimization Algorithms over Graphs NIPS 2017
Is the Bellman residual a bad proxy? NIPS 2017
Compatible Reward Inverse Reinforcement Learning NIPS 2017
Adaptive Batch Size for Safe Policy Gradients NIPS 2017
Cold-Start Reinforcement Learning with Softmax Policy Gradient NIPS 2017
Bridging the Gap Between Value and Policy Based Reinforcement Learning NIPS 2017
Natural Value Approximators: Learning when to Trust Past Estimates NIPS 2017
Value Prediction Network NIPS 2017
Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CORL 2017
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously CORL 2017
Learning Robot Objectives from Physical Human Interaction CORL 2017
Optimizing Long-term Predictions for Model-based Policy Search CORL 2017
Learning End-to-end Multimodal Sensor Policies for Autonomous Navigation CORL 2017
Mutual Alignment Transfer Learning CORL 2017
Hierarchical Reinforcement Learning with Parameters CORL 2017
Emergent Behaviors in Mixed-Autonomy Traffic CORL 2017
DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations CORL 2017
Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments CORL 2017
Reverse Curriculum Generation for Reinforcement Learning CORL 2017
Semi-Supervised QA with Generative Domain-Adaptive Nets ACL 2017