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 751–775 of 15113 papers

TitleStatusHype
Continual Reinforcement Learning with Multi-Timescale ReplayCode1
Continuous Deep Q-Learning with Model-based AccelerationCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous ControlCode1
Co-Reinforcement Learning for Unified Multimodal Understanding and GenerationCode1
Deep RL Agent for a Real-Time Action Strategy GameCode1
Curious Hierarchical Actor-Critic Reinforcement LearningCode1
Deep Symbolic Superoptimization Without Human KnowledgeCode1
Accelerating lifelong reinforcement learning via reshaping rewardsCode1
Agent57: Outperforming the Atari Human BenchmarkCode1
Adversarial Policies: Attacking Deep Reinforcement LearningCode1
Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional CurriculumCode1
Contextualized Rewriting for Text SummarizationCode1
Denoised MDPs: Learning World Models Better Than the World ItselfCode1
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting AgentCode1
Deployment-Efficient Reinforcement Learning via Model-Based Offline OptimizationCode1
Active MR k-space Sampling with Reinforcement LearningCode1
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement LearningCode1
Contextualize Me -- The Case for Context in Reinforcement LearningCode1
Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-InteractionCode1
Constrained Variational Policy Optimization for Safe Reinforcement LearningCode1
Constructions in combinatorics via neural networksCode1
Adversarially Trained Actor Critic for Offline Reinforcement LearningCode1
AI2-THOR: An Interactive 3D Environment for Visual AICode1
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement LearningCode1
Show:102550
← PrevPage 31 of 605Next →

Benchmark Results

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