SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Showing 90519100 of 15113 papers

TitleStatusHype
Representation Balancing Offline Model-based Reinforcement Learning0
Optimizing Information Bottleneck in Reinforcement Learning: A Stein Variational Approach0
Uncertainty Weighted Offline Reinforcement Learning0
Unsupervised Task Clustering for Multi-Task Reinforcement LearningCode0
Meta-Reinforcement Learning With Informed Policy Regularization0
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks0
Optimistic Exploration with Backward Bootstrapped Bonus for Deep Reinforcement Learning0
Practical Marginalized Importance Sampling with the Successor Representation0
On Trade-offs of Image Prediction in Visual Model-Based Reinforcement Learning0
Scalable Bayesian Inverse Reinforcement Learning by Auto-Encoding Reward0
The Skill-Action Architecture: Learning Abstract Action Embeddings for Reinforcement Learning0
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study0
Reinforcement Learning Based Asymmetrical DNN Modularization for Optimal Loading0
Reinforcement Learning for Control with Probabilistic Stability Guarantee0
Robust Imitation via Decision-Time Planning0
Prior Preference Learning From Experts: Designing A Reward with Active Inference0
Robust Multi-Agent Reinforcement Learning Driven by Correlated Equilibrium0
Regioned Episodic Reinforcement Learning0
Robust Offline Reinforcement Learning from Low-Quality Data0
Re-examining Routing Networks for Multi-task Learning0
Success-Rate Targeted Reinforcement Learning by Disorientation Penalty0
ScheduleNet: Learn to Solve MinMax mTSP Using Reinforcement Learning with Delayed Reward0
Plan-Based Asymptotically Equivalent Reward Shaping0
Unsupervised Active Pre-Training for Reinforcement Learning0
RECONNAISSANCE FOR REINFORCEMENT LEARNING WITH SAFETY CONSTRAINTS0
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic0
Provable Rich Observation Reinforcement Learning with Combinatorial Latent States0
R-LAtte: Attention Module for Visual Control via Reinforcement Learning0
Sample efficient Quality Diversity for neural continuous control0
Simple Augmentation Goes a Long Way: ADRL for DNN Quantization0
Offline Policy Optimization with Variance Regularization0
Monte-Carlo Planning and Learning with Language Action Value Estimates0
Reinforcement Learning with Bayesian Classifiers: Efficient Skill Learning from Outcome Examples0
Optimistic Policy Optimization with General Function Approximations0
Weighted Bellman Backups for Improved Signal-to-Noise in Q-Updates0
PODS: Policy Optimization via Differentiable Simulation0
What are the Statistical Limits of Batch RL with Linear Function Approximation?0
Learning a Transferable Scheduling Policy for Various Vehicle Routing Problems based on Graph-centric Representation Learning0
Attention-driven Robotic Manipulation0
Fine-Tuning Offline Reinforcement Learning with Model-Based Policy Optimization0
Learning Active Learning in the Batch-Mode Setup with Ensembles of Active Learning Agents0
Coordinated Multi-Agent Exploration Using Shared Goals0
Improving Learning to Branch via Reinforcement Learning0
Approximating Pareto Frontier through Bayesian-optimization-directed Robust Multi-objective Reinforcement Learning0
Communication in Multi-Agent Reinforcement Learning: Intention Sharing0
Distributional Reinforcement Learning for Risk-Sensitive Policies0
Aspect-based Sentiment Classification via Reinforcement Learning0
Grounding Language to Entities for Generalization in Reinforcement Learning0
Learning Latent Landmarks for Generalizable Planning0
Adaptive Learning Rates for Multi-Agent Reinforcement Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76Unverified
2PPOMean Normalized Performance0.58Unverified