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 3151–3200 of 15113 papers

TitleStatusHype
Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation—0
Curiosity-driven reinforcement learning with homeostatic regulation—0
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning—0
A Survey on Deep Reinforcement Learning for Data Processing and Analytics—0
A Survey on Dialog Management: Recent Advances and Challenges—0
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation—0
CROPS: A Deployable Crop Management System Over All Possible State Availabilities—0
Curious iLQR: Resolving Uncertainty in Model-based RL—0
A Survey of Demonstration Learning—0
A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions—0
Agent Spaces—0
Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation—0
Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback—0
Curriculum-based Deep Reinforcement Learning for Quantum Control—0
A Survey of Deep Reinforcement Learning in Video Games—0
Curriculum Based Reinforcement Learning of Grid Topology Controllers to Prevent Thermal Cascading—0
A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning—0
Curriculum goal masking for continuous deep reinforcement learning—0
Curriculum-Guided Antifragile Reinforcement Learning for Secure UAV Deconfliction under Observation-Space Attacks—0
Curriculum in Gradient-Based Meta-Reinforcement Learning—0
Curriculum Learning Based on Reward Sparseness for Deep Reinforcement Learning of Task Completion Dialogue Management—0
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey—0
Curriculum Learning with a Progression Function—0
Curriculum Offline Imitating Learning—0
Critic PI2: Master Continuous Planning via Policy Improvement with Path Integrals and Deep Actor-Critic Reinforcement Learning—0
A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles—0
Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution—0
Curriculum-RLAIF: Curriculum Alignment with Reinforcement Learning from AI Feedback—0
A Survey on Reinforcement Learning for Recommender Systems—0
CVLight: Decentralized Learning for Adaptive Traffic Signal Control with Connected Vehicles—0
CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem—0
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation—0
Cycle Consistency Driven Object Discovery—0
A Survey on Reinforcement Learning Methods in Character Animation—0
A Survey on Reinforcement Learning Security with Application to Autonomous Driving—0
CycLight: learning traffic signal cooperation with a cycle-level strategy—0
CyGIL: A Cyber Gym for Training Autonomous Agents over Emulated Network Systems—0
A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systems—0
d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning—0
Deep Reinforcement Learning for Chatbots Using Clustered Actions and Human-Likeness Rewards—0
D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning—0
A Survey on Traffic Signal Control Methods—0
DACOM: Learning Delay-Aware Communication for Multi-Agent Reinforcement Learning—0
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning—0
Criticality-Based Varying Step-Number Algorithm for Reinforcement Learning—0
Agent Probing Interaction Policies—0
Credit-cognisant reinforcement learning for multi-agent cooperation—0
DanZero: Mastering GuanDan Game with Reinforcement Learning—0
DAQN: Deep Auto-encoder and Q-Network—0
Credit Assignment with Meta-Policy Gradient for Multi-Agent Reinforcement Learning—0
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Benchmark Results

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