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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1876–1900 of 15113 papers

TitleStatusHype
Robust Deep Reinforcement Learning for Quadcopter ControlCode1
An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy SearchCode1
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement LearningCode1
Improved Representation of Asymmetrical Distances with Interval Quasimetric EmbeddingsCode1
Avalanche RL: a Continual Reinforcement Learning LibraryCode1
Avalon: A Benchmark for RL Generalization Using Procedurally Generated WorldsCode1
A Minimalist Approach to Offline Reinforcement LearningCode1
Generative Adversarial Imitation LearningCode1
Implicit Unlikelihood Training: Improving Neural Text Generation with Reinforcement LearningCode1
Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement LearningCode1
Robust Reinforcement Learning on State Observations with Learned Optimal AdversaryCode1
Improving and Benchmarking Offline Reinforcement Learning AlgorithmsCode1
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICsCode1
ROLL: Visual Self-Supervised Reinforcement Learning with Object ReasoningCode1
Geometric Deep Reinforcement Learning for Dynamic DAG SchedulingCode1
Benchmarking Reinforcement Learning Techniques for Autonomous NavigationCode1
RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture SearchCode1
Implicit Distributional Reinforcement LearningCode1
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPOCode1
Giving Up Control: Neurons as Reinforcement Learning AgentsCode1
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic EnvironmentsCode1
Geometric Multimodal Contrastive Representation LearningCode1
GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical ReasoningCode1
Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement LearningCode1
Implementation Matters in Deep RL: A Case Study on PPO and TRPOCode1
Show:102550
← PrevPage 76 of 605Next →

Benchmark Results

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