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 4576–4600 of 15113 papers

TitleStatusHype
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-TuningCode0
On the Implementation of a Reinforcement Learning-based Capacity Sharing Algorithm in O-RANCode0
Self Punishment and Reward Backfill for Deep Q-LearningCode0
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended OutcomesCode0
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement LearningCode0
Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot NavigationCode0
What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?Code0
On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ,λ))-GACode0
Reinforcement learning for multi-item retrieval in the puzzle-based storage systemCode0
Self-Supervised State-Control through Intrinsic Mutual Information RewardsCode0
When Does Neuroevolution Outcompete Reinforcement Learning in Transfer Learning Tasks?Code0
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal AbstractionsCode0
MicroRacer: a didactic environment for Deep Reinforcement LearningCode0
PPO-CMA: Proximal Policy Optimization with Covariance Matrix AdaptationCode0
PPO Dash: Improving Generalization in Deep Reinforcement LearningCode0
Mid-flight Propeller Failure Detection and Control of Propeller-deficient Quadcopter using Reinforcement LearningCode0
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement LearningCode0
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RLCode0
When to Sense and Control? A Time-adaptive Approach for Continuous-Time RLCode0
Semifactual Explanations for Reinforcement LearningCode0
Semi-Markov Offline Reinforcement Learning for HealthcareCode0
Where Do You Think You're Going?: Inferring Beliefs about Dynamics from BehaviorCode0
Optimality Inductive Biases and Agnostic Guidelines for Offline Reinforcement LearningCode0
Semi-Offline Reinforcement Learning for Optimized Text GenerationCode0
Semi-supervised Deep Reinforcement Learning in Support of IoT and Smart City ServicesCode0
Show:102550
← PrevPage 184 of 605Next →

Benchmark Results

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