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 2251–2275 of 15113 papers

TitleStatusHype
End-to-End Urban Driving by Imitating a Reinforcement Learning CoachCode1
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without SacrificesCode1
Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement LearningCode1
Bridging Imagination and Reality for Model-Based Deep Reinforcement LearningCode1
Information Directed Reward Learning for Reinforcement LearningCode1
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their SolutionsCode1
An Inductive Bias for Distances: Neural Nets that Respect the Triangle InequalityCode1
Enhancing data efficiency in reinforcement learning: a novel imagination mechanism based on mesh information propagationCode1
Offline Reinforcement Learning for Visual NavigationCode1
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement LearningCode1
Bridging State and History Representations: Understanding Self-Predictive RLCode1
Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical InvestigationCode1
Behaviour Discovery and Attribution for Explainable Reinforcement Learning—0
Behaviour-conditioned policies for cooperative reinforcement learning tasks—0
Analyzing Behaviors of Mixed Traffic via Reinforcement Learning at Unsignalized Intersections—0
Behavioural Cloning in VizDoom—0
Behavior Regularized Offline Reinforcement Learning—0
Adaptive Tree Backup Algorithms for Temporal-Difference Reinforcement Learning—0
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning—0
Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning—0
Behavior Priors for Efficient Reinforcement Learning—0
Analytically Tractable Bayesian Deep Q-Learning—0
Adaptive Transit Signal Priority based on Deep Reinforcement Learning and Connected Vehicles in a Traffic Microsimulation Environment—0
A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management—0
Behavior Planning at Urban Intersections through Hierarchical Reinforcement Learning—0
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Benchmark Results

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