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Reinforcement Learning
83 directly classified papers
Subtopics
Applications (40)
Methods (9)
Papers per year
2006: 1
2007: 1
2008: 4
2010: 3
2011: 4
2012: 1
2014: 1
2017: 1
2018: 2
2019: 6
2020: 15
2021: 10
2022: 9
2023: 6
2024: 11
2025: 5
2026: 3
Papers
Learning Intrinsic Rewards as a Bi-Level Optimization Problem
UAI 2020
Learning Behaviors with Uncertain Human Feedback
UAI 2020
What Can Learned Intrinsic Rewards Capture?
ICML 2020
Neural Contextual Bandits with UCB-based Exploration
ICML 2020
Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
ICML 2020
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning
AAAI 2020
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks
AAAI 2020
Uncorrected Least-Squares Temporal Difference with Lambda-Return
AAAI 2020
BAR — A Reinforcement Learning Agent for Bounding-Box Automated Refinement
AAAI 2020
Learning to Walk Via Deep Reinforcement Learning
RSS 2019
On-Policy Robot Imitation Learning from a Converging Supervisor
CORL 2019
To Follow or not to Follow: Selective Imitation Learning from Observations
CORL 2019
Policy Continuation with Hindsight Inverse Dynamics
NIPS 2019
Data Efficient Reinforcement Learning for Legged Robots
CORL 2019
Attention-Aware Sampling via Deep Reinforcement Learning for Action Recognition
AAAI 2019
Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories
CORL 2018
Policies Modulating Trajectory Generators
CORL 2018
Unifying Task Specification in Reinforcement Learning
ICML 2017
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics
NIPS 2014
Learned Prioritization for Trading Off Accuracy and Speed
NIPS 2012
Improving Policy Gradient Estimates with Influence Information
ACML 2011
Continuous Rapid Action Value Estimates
ACML 2011
Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning
RSS 2011
Learning to Agglomerate Superpixel Hierarchies
NIPS 2011
On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient
NIPS 2010
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