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 13101–13150 of 15113 papers

TitleStatusHype
Causal Reasoning from Meta-reinforcement LearningCode0
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) CompetitionCode0
Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning—0
Reinforcement Learning of Markov Decision Processes with Peak Constraints—0
Towards Learning to Imitate from a Single Video Demonstration—0
Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the DQN TargetCode0
Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learning—0
Fast, Accurate and Lightweight Super-Resolution with Neural Architecture SearchCode0
A Short Survey on Probabilistic Reinforcement Learning—0
Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in VideosCode0
Towards Physically Safe Reinforcement Learning under Supervision—0
Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems—0
WALL-E: An Efficient Reinforcement Learning Research FrameworkCode0
On-Policy Trust Region Policy Optimisation with Replay BuffersCode0
Multi-agent Reinforcement Learning Embedded Game for the Optimization of Building Energy Control and Power System Planning—0
Amplifying the Imitation Effect for Reinforcement Learning of UCAV's Mission ExecutionCode0
Evolutionarily-Curated Curriculum Learning for Deep Reinforcement Learning Agents—0
Representation Learning on Graphs: A Reinforcement Learning Application—0
Transfer Learning for Prosthetics Using Imitation LearningCode0
Energy-Efficient Thermal Comfort Control in Smart Buildings via Deep Reinforcement LearningCode0
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning—0
Comparing Knowledge-based Reinforcement Learning to Neural Networks in a Strategy Game—0
Improving Coordination in Small-Scale Multi-Agent Deep Reinforcement Learning through Memory-driven CommunicationCode0
An investigation of model-free planningCode0
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning—0
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator—0
Motion Perception in Reinforcement Learning with Dynamic Objects—0
A New Tensioning Method using Deep Reinforcement Learning for Surgical Pattern Cutting—0
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning—0
Risk-Aware Active Inverse Reinforcement LearningCode0
A* Tree Search for Portfolio Management—0
A dual mode adaptive basal-bolus advisor based on reinforcement learning—0
Credit Assignment Techniques in Stochastic Computation Graphs—0
Exploring applications of deep reinforcement learning for real-world autonomous driving systems—0
What Should I Do Now? Marrying Reinforcement Learning and Symbolic Planning—0
Self-Learning Exploration and Mapping for Mobile Robots via Deep Reinforcement LearningCode0
Recurrent Control Nets for Deep Reinforcement Learning—0
Deep Reinforcement Learning for Imbalanced ClassificationCode0
Hierarchical Reinforcement Learning via Advantage-Weighted Information MaximizationCode0
Accelerating Goal-Directed Reinforcement Learning by Model Characterization—0
Optimal Decision-Making in Mixed-Agent Partially Observable Stochastic Environments via Reinforcement Learning—0
Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding—0
Imminent Collision Mitigation with Reinforcement Learning and Vision—0
A Computational Framework for Motor Skill Acquisition—0
Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning—0
Complementary reinforcement learning towards explainable agents—0
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds—0
Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications—0
Meta Reinforcement Learning with Distribution of Exploration Parameters Learned by Evolution Strategies—0
State representation learning with recurrent capsule networks—0
Show:102550
← PrevPage 263 of 303Next →

Benchmark Results

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