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 4651–4675 of 15113 papers

TitleStatusHype
Reinforcement Learning for Solving the Vehicle Routing ProblemCode0
Multiagent Reinforcement Learning based Energy Beamforming ControlCode0
Predictive World Models from Real-World Partial ObservationsCode0
Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models—0
Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks—0
Reinforced Multi-task Approach for Multi-hop Question Generation—0
Reinforced Pedestrian Attribute Recognition with Group Optimization Reward—0
Reinforced Self-Training (ReST) for Language Modeling—0
Reinforced Training Data Selection for Domain Adaptation—0
Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API—0
Reinforced Video Captioning with Entailment Rewards—0
Reinforced Workload Distribution Fairness—0
Reinforcement and Imitation Learning via Interactive No-Regret Learning—0
Reinforcement-based frugal learning for satellite image change detection—0
Reinforcement Evolutionary Learning Method for self-learning—0
Reinforcement Explanation Learning—0
Reinforcement Leaning for Infinite-Dimensional Systems—0
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound—0
Reinforcement Learning: a Comparison of UCB Versus Alternative Adaptive Policies—0
Reinforcement Learning Agent Design and Optimization with Bandwidth Allocation Model—0
Reinforcement Learning Agents for Ubisoft's Roller Champions—0
Reinforcement Learning Agent Training with Goals for Real World Tasks—0
Reinforcement Learning Algorithm for Traffic Steering in Heterogeneous Network—0
Reinforcement Learning Algorithms: An Overview and Classification—0
Reinforcement Learning Algorithm Selection—0
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Benchmark Results

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