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 11001–11050 of 15113 papers

TitleStatusHype
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement LearningCode1
Learning Force Control for Contact-rich Manipulation Tasks with Rigid Position-controlled Robots—0
Fully Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks—0
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement LearningCode0
Learning When and Where to Zoom with Deep Reinforcement LearningCode1
Learning Near Optimal Policies with Low Inherent Bellman Error—0
Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts—0
TAdam: A Robust Stochastic Gradient OptimizerCode0
Mixed Reinforcement Learning with Additive Stochastic Uncertainty—0
A Self-Tuning Actor-Critic Algorithm—0
On Catastrophic Interference in Atari 2600 GamesCode0
Deep Reinforcement Learning for FlipIt Security Game—0
Reinforcement Learning through Active Inference—0
Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications—0
Towards Modular Algorithm Induction—0
Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games—0
Learning in Markov Decision Processes under Constraints—0
A Visual Communication Map for Multi-Agent Deep Reinforcement Learning—0
Autonomous robotic nanofabrication with reinforcement learningCode0
Assembly robots with optimized control stiffness through reinforcement learning—0
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
Analysis of diversity-accuracy tradeoff in image captioningCode1
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain—0
Review, Analysis and Design of a Comprehensive Deep Reinforcement Learning Framework—0
Training Adversarial Agents to Exploit Weaknesses in Deep Control PoliciesCode0
Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning—0
Reinforcement Learning of Risk-Constrained Policies in Markov Decision ProcessesCode0
Neural Ordinary Differential Equation Value Networks for Parametrized Action Spaces—0
Optimistic Exploration even with a Pessimistic InitialisationCode1
Using Reinforcement Learning in the Algorithmic Trading ProblemCode1
Cautious Reinforcement Learning with Logical Constraints—0
Efficient reinforcement learning control for continuum robots based on Inexplicit Prior KnowledgeCode0
Generalized Hindsight for Reinforcement Learning—0
Mid-flight Propeller Failure Detection and Control of Propeller-deficient Quadcopter using Reinforcement LearningCode0
When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning—0
Scalable Multi-Task Imitation Learning with Autonomous Improvement—0
Whole-Body Control of a Mobile Manipulator using End-to-End Reinforcement LearningCode1
Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization—0
On Reinforcement Learning for Turn-based Zero-sum Markov Games—0
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements—0
Rewriting History with Inverse RL: Hindsight Inference for Policy ImprovementCode1
Off-Policy Deep Reinforcement Learning with Analogous Disentangled ExplorationCode0
Reward Shaping for Human Learning via Inverse Reinforcement LearningCode0
G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning—0
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity—0
Safe reinforcement learning for probabilistic reachability and safety specifications: A Lyapunov-based approachCode0
Millimeter Wave Communications with an Intelligent Reflector: Performance Optimization and Distributional Reinforcement Learning—0
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement LearningCode1
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic—0
Wireless 2.0: Towards an Intelligent Radio Environment Empowered by Reconfigurable Meta-Surfaces and Artificial Intelligence—0
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Benchmark Results

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