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Reinforcement Learning
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Robotics
2069 directly classified papers
Papers per year
2005: 4
2006: 13
2007: 13
2008: 14
2009: 4
2010: 14
2011: 15
2012: 20
2013: 20
2014: 18
2015: 14
2016: 22
2017: 53
2018: 84
2019: 166
2020: 215
2021: 282
2022: 268
2023: 342
2024: 254
2025: 193
2026: 41
Papers
Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search
IJCAI 2019
Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time
AAAI 2019
Influence of State-Variable Constraints on Partially Observable Monte Carlo Planning
IJCAI 2019
Successor Options: An Option Discovery Framework for Reinforcement Learning
IJCAI 2019
Incremental Learning of Planning Actions in Model-Based Reinforcement Learning
IJCAI 2019
Autoregressive Policies for Continuous Control Deep Reinforcement Learning
IJCAI 2019
MineRL: A Large-Scale Dataset of Minecraft Demonstrations
IJCAI 2019
Park: An Open Platform for Learning-Augmented Computer Systems
NIPS 2019
A Composable Specification Language for Reinforcement Learning Tasks
NIPS 2019
A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation
NIPS 2019
Planning with Goal-Conditioned Policies
NIPS 2019
Control What You Can: Intrinsically Motivated Task-Planning Agent
NIPS 2019
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
NIPS 2019
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
NIPS 2019
Curriculum-guided Hindsight Experience Replay
NIPS 2019
Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes
NIPS 2019
Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards
IJCAI 2019
Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards
NIPS 2019
Scalable Global Optimization via Local Bayesian Optimization
NIPS 2019
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards
NIPS 2019
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
NIPS 2019
Budgeted Reinforcement Learning in Continuous State Space
NIPS 2019
DAC: The Double Actor-Critic Architecture for Learning Options
NIPS 2019
Learning Robust Options by Conditional Value at Risk Optimization
NIPS 2019
Policy Continuation with Hindsight Inverse Dynamics
NIPS 2019
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