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

Showing 1205112100 of 15113 papers

TitleStatusHype
Safe Reinforcement Learning-based Control for Hydrogen Diesel Dual-Fuel Engines0
Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances0
Safe reinforcement learning control for continuous-time nonlinear systems without a backup controller0
Safe Reinforcement Learning for an Energy-Efficient Driver Assistance System0
A Safe Reinforcement Learning Architecture for Antenna Tilt Optimisation0
Safe Reinforcement Learning for a Robot Being Pursued but with Objectives Covering More Than Capture-avoidance0
Safe Reinforcement Learning for Autonomous Vehicles through Parallel Constrained Policy Optimization0
Safe Reinforcement Learning for Grid Voltage Control0
Safe Reinforcement Learning for Legged Locomotion0
Safe reinforcement learning for multi-energy management systems with known constraint functions0
Safe Reinforcement Learning for Power System Control: A Review0
Safe Reinforcement Learning for Real-World Engine Control0
Safe Reinforcement Learning in a Simulated Robotic Arm0
Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space0
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction0
Safe Reinforcement Learning on Autonomous Vehicles0
Safe Reinforcement Learning through Meta-learned Instincts0
Safe Reinforcement Learning using Data-Driven Predictive Control0
Safe Reinforcement Learning Using Robust Action Governor0
Safe Reinforcement Learning via Confidence-Based Filters0
Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?0
Safe Reinforcement Learning via Shielding under Partial Observability0
Safe Reinforcement Learning with Probabilistic Control Barrier Functions for Ramp Merging0
Safe Reinforcement Learning with Chance-constrained Model Predictive Control0
Safe Reinforcement Learning with Contrastive Risk Prediction0
Safe Reinforcement Learning with Dual Robustness0
Safe Reinforcement Learning with Free-form Natural Language Constraints and Pre-Trained Language Models0
Safe Reinforcement Learning with Learned Non-Markovian Safety Constraints0
Safe Reinforcement Learning with Linear Function Approximation0
Safe Reinforcement Learning with Minimal Supervision0
Safe Reinforcement Learning with Mixture Density Network: A Case Study in Autonomous Highway Driving0
Safe Reinforcement Learning with Model Uncertainty Estimates0
Safe Reinforcement Learning with Natural Language Constraints0
An adaptive safety layer with hard constraints for safe reinforcement learning in multi-energy management systems0
Learning for MPC with Stability & Safety Guarantees0
SafeRL-Kit: Evaluating Efficient Reinforcement Learning Methods for Safe Autonomous Driving0
Safe Trajectory Planning Using Reinforcement Learning for Self Driving0
Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving0
Safety aware model-based reinforcement learning for optimal control of a class of output-feedback nonlinear systems0
Safety-Aware Multi-Agent Apprenticeship Learning0
Safe Autonomous Racing via Approximate Reachability on Ego-vision0
Safety-Aware Reinforcement Learning for Electric Vehicle Charging Station Management in Distribution Network0
Safety-Aware Reinforcement Learning for Control via Risk-Sensitive Action-Value Iteration and Quantile Regression0
Safety Aware Reinforcement Learning (SARL)0
Safety-Aware Task Composition for Discrete and Continuous Reinforcement Learning0
Safety Correction from Baseline: Towards the Risk-aware Policy in Robotics via Dual-agent Reinforcement Learning0
Safety-Enhanced Self-Learning for Optimal Power Converter Control0
Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance0
Safety Filtering for Reinforcement Learning-based Adaptive Cruise Control0
Safety-guaranteed Reinforcement Learning based on Multi-class Support Vector Machine0
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Benchmark Results

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