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 8401–8450 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning Based Controller for Active Heave Compensation—0
Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning—0
The Atari Data ScraperCode0
Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog ManagementCode0
Symmetry reduction for deep reinforcement learning active control of chaotic spatiotemporal dynamics—0
CropGym: a Reinforcement Learning Environment for Crop ManagementCode1
Learning Sampling Policy for Faster Derivative Free Optimization—0
A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline—0
Inverse Reinforcement Learning: A Control Lyapunov Approach—0
Jamming-Resilient Path Planning for Multiple UAVs via Deep Reinforcement Learning—0
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning—0
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural NetworksCode1
Efficient time stepping for numerical integration using reinforcement learningCode0
ACERAC: Efficient reinforcement learning in fine time discretization—0
A Bayesian Approach to Reinforcement Learning of Vision-Based Vehicular ControlCode0
A Reinforcement Learning Environment For Job-Shop SchedulingCode1
Arena-Rosnav: Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation SystemsCode1
Optimal Market Making by Reinforcement LearningCode1
The Value of Planning for Infinite-Horizon Model Predictive ControlCode0
Unsupervised Visual Attention and Invariance for Reinforcement Learning—0
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation—0
Generating Multi-type Temporal Sequences to Mitigate Class-imbalanced ProblemCode0
Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation—0
Improving Robustness of Deep Reinforcement Learning Agents: Environment Attack based on the Critic NetworkCode0
Risk-Conditioned Distributional Soft Actor-Critic for Risk-Sensitive Navigation—0
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable PhysicsCode1
Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning—0
Progressive extension of reinforcement learning action dimension for asymmetric assembly tasks—0
Design and implementation of an environment for Learning to Run a Power Network (L2RPN)Code1
Approximate Robust NMPC using Reinforcement Learning—0
Distributed Deep Reinforcement Learning for Collaborative Spectrum Sharing—0
Data-Driven Simulation of Ride-Hailing Services using Imitation and Reinforcement Learning—0
MPC-based Reinforcement Learning for Economic Problems with Application to Battery Storage—0
Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking—0
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTSCode1
AMP: Adversarial Motion Priors for Stylized Physics-Based Character ControlCode2
A Dual-Critic Reinforcement Learning Framework for Frame-level Bit Allocation in HEVC/H.265—0
Machine Learning Applications in the Routing in Computer Networks—0
NQMIX: Non-monotonic Value Function Factorization for Deep Multi-Agent Reinforcement Learning—0
Distributed Reinforcement Learning for Age of Information Minimization in Real-Time IoT Systems—0
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems—0
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation—0
Influencing Reinforcement Learning through Natural Language GuidanceCode0
Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA—0
A Dynamics Perspective of Pursuit-Evasion Games of Intelligent Agents with the Ability to Learn—0
Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability—0
Federated Double Deep Q-learning for Joint Delay and Energy Minimization in IoT networks—0
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?Code0
Low Dose Helical CBCT denoising by using domain filtering with deep reinforcement learning—0
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Benchmark Results

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