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

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Showing 11276–11300 of 15113 papers

TitleStatusHype
Reinforcement Learning of Risk-Constrained Policies in Markov Decision ProcessesCode0
Training Adversarial Agents to Exploit Weaknesses in Deep Control PoliciesCode0
Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning—0
Review, Analysis and Design of a Comprehensive Deep Reinforcement Learning Framework—0
Towards Modular Algorithm Induction—0
Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications—0
Autonomous robotic nanofabrication with reinforcement learningCode0
Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image—0
Learning in Markov Decision Processes under Constraints—0
Assembly robots with optimized control stiffness through reinforcement learning—0
Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games—0
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain—0
A Visual Communication Map for Multi-Agent Deep Reinforcement Learning—0
Generalized Hindsight for Reinforcement Learning—0
Efficient reinforcement learning control for continuum robots based on Inexplicit Prior KnowledgeCode0
Cautious Reinforcement Learning with Logical Constraints—0
Neural Ordinary Differential Equation Value Networks for Parametrized Action Spaces—0
When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning—0
Mid-flight Propeller Failure Detection and Control of Propeller-deficient Quadcopter using Reinforcement LearningCode0
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements—0
Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization—0
On Reinforcement Learning for Turn-based Zero-sum Markov Games—0
Scalable Multi-Task Imitation Learning with Autonomous Improvement—0
Off-Policy Deep Reinforcement Learning with Analogous Disentangled ExplorationCode0
G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning—0
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Benchmark Results

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