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 46514700 of 15113 papers

TitleStatusHype
Regret Bounds for Risk-Sensitive Reinforcement Learning0
Multi-Object Navigation with dynamically learned neural implicit representationsCode1
Multiagent Reinforcement Learning Based on Fusion-Multiactor-Attention-Critic for Multiple-Unmanned-Aerial-Vehicle Navigation ControlCode1
Simulating Coverage Path Planning with Roomba0
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies0
Long N-step Surrogate Stage Reward to Reduce Variances of Deep Reinforcement Learning in Complex Problems0
A policy gradient approach for Finite Horizon Constrained Markov Decision ProcessesCode0
Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy GradientCode0
Benchmarking Reinforcement Learning Techniques for Autonomous NavigationCode1
A Comprehensive Survey of Data Augmentation in Visual Reinforcement LearningCode1
In-Hand Object Rotation via Rapid Motor AdaptationCode2
Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning0
Experiential Explanations for Reinforcement LearningCode0
Equivalence of Optimality Criteria for Markov Decision Process and Model Predictive Control0
Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement LearningCode1
The Role of Coverage in Online Reinforcement Learning0
Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweeningCode1
State Advantage Weighting for Offline RL0
Dynamically meeting performance objectives for multiple services on a service mesh0
Cognitive Models as Simulators: The Case of Moral Decision-Making0
Winner Takes It All: Training Performant RL Populations for Combinatorial OptimizationCode1
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement LearningCode1
Large Language Models can Implement Policy Iteration0
Conservative Bayesian Model-Based Value Expansion for Offline Policy OptimizationCode0
Exploration Policies for On-the-Fly Controller Synthesis: A Reinforcement Learning ApproachCode0
Reinforcement Learning Approach for Multi-Agent Flexible Scheduling Problems0
Multi-agent Deep Covering Skill Discovery0
BAFFLE: Hiding Backdoors in Offline Reinforcement Learning DatasetsCode1
How to Enable Uncertainty Estimation in Proximal Policy Optimization0
Advice Conformance Verification by Reinforcement Learning agents for Human-in-the-Loop0
Algorithmic Trading Using Continuous Action Space Deep Reinforcement Learning0
Low-Thrust Orbital Transfer using Dynamics-Agnostic Reinforcement Learning0
Digital Human Interactive Recommendation Decision-Making Based on Reinforcement Learning0
Deep Inventory Management0
Exploration via Planning for Information about the Optimal TrajectoryCode1
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill DiscoveryCode1
Lyapunov Function Consistent Adaptive Network Signal Control with Back Pressure and Reinforcement Learning0
Rainier: Reinforced Knowledge Introspector for Commonsense Question AnsweringCode1
Meta Reinforcement Learning for Optimal Design of Legged Robots0
Reinforcement Learning with Large Action Spaces for Neural Machine Translation0
Learning Algorithms for Intelligent Agents and Mechanisms0
Deep Reinforcement Learning based Evasion Generative Adversarial Network for Botnet DetectionCode1
Distributionally Adaptive Meta Reinforcement Learning0
Discovering faster matrix multiplication algorithms with reinforcement learningCode4
A Novel Entropy-Maximizing TD3-based Reinforcement Learning for Automatic PID Tuning0
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic ControlCode1
DreamShard: Generalizable Embedding Table Placement for Recommender SystemsCode1
Query The Agent: Improving sample efficiency through epistemic uncertainty estimation0
Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement LearningCode0
Real-Time Reinforcement Learning for Vision-Based Robotics Utilizing Local and Remote ComputersCode1
Show:102550
← PrevPage 94 of 303Next →

Benchmark Results

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