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 2626–2650 of 15113 papers

TitleStatusHype
Autonomous Driving in Reality with Reinforcement Learning and Image Translation—0
Autonomous Control of a Particle Accelerator using Deep Reinforcement Learning—0
Alternating Good-for-MDP Automata—0
A Bayesian Framework of Deep Reinforcement Learning for Joint O-RAN/MEC Orchestration—0
Cost-Sensitive Exploration in Bayesian Reinforcement Learning—0
AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks—0
Autonomous Braking and Throttle System: A Deep Reinforcement Learning Approach for Naturalistic Driving—0
Adaptive model selection in photonic reservoir computing by reinforcement learning—0
Autonomous Attack Mitigation for Industrial Control Systems—0
Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning—0
AlphaStar: An Evolutionary Computation Perspective—0
A Bayesian Approach to Robust Reinforcement Learning—0
Autonomous Algorithm for Training Autonomous Vehicles with Minimal Human Intervention—0
Autonomous Air Traffic Controller: A Deep Multi-Agent Reinforcement Learning Approach—0
AlphaSnake: Policy Iteration on a Nondeterministic NP-hard Markov Decision Process—0
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning—0
Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing—0
AlphaSeq: Sequence Discovery with Deep Reinforcement Learning—0
A Coarse to Fine Question Answering System based on Reinforcement Learning—0
Correlation Priors for Reinforcement Learning—0
Automating Turbulence Modeling by Multi-Agent Reinforcement Learning—0
Automating the resolution of flight conflicts: Deep reinforcement learning in service of air traffic controllers—0
AlphaRouter: Quantum Circuit Routing with Reinforcement Learning and Tree Search—0
Automating Staged Rollout with Reinforcement Learning—0
Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning—0
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Benchmark Results

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