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 67516800 of 15113 papers

TitleStatusHype
Dynamic Value Estimation for Single-Task Multi-Scene Reinforcement Learning0
Dynamic Virtual Network Embedding Algorithm based on Graph Convolution Neural Network and Reinforcement Learning0
Dyna Planning using a Feature Based Generative Model0
Dyna-T: Dyna-Q and Upper Confidence Bounds Applied to Trees0
DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning0
EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization0
EasyRL: A Simple and Extensible Reinforcement Learning Framework0
EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning0
Eco-driving for Electric Connected Vehicles at Signalized Intersections: A Parameterized Reinforcement Learning approach0
EcoLight: Intersection Control in Developing Regions Under Extreme Budget and Network Constraints0
Ecological Reinforcement Learning0
ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning0
Economical Precise Manipulation and Auto Eye-Hand Coordination with Binocular Visual Reinforcement Learning0
e-COP : Episodic Constrained Optimization of Policies0
Eco-Vehicular Edge Networks for Connected Transportation: A Distributed Multi-Agent Reinforcement Learning Approach0
Eden: A Unified Environment Framework for Booming Reinforcement Learning Algorithms0
Edge AI-Powered Real-Time Decision-Making for Autonomous Vehicles in Adverse Weather Conditions0
Edge-Cloud Cooperation for DNN Inference via Reinforcement Learning and Supervised Learning0
Edge-Compatible Reinforcement Learning for Recommendations0
EdgeRL: Reinforcement Learning-driven Deep Learning Model Inference Optimization at Edge0
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning0
EEG_RL-Net: Enhancing EEG MI Classification through Reinforcement Learning-Optimised Graph Neural Networks0
Generalization through Diversity: Improving Unsupervised Environment Design0
Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization0
Effective Medical Test Suggestions Using Deep Reinforcement Learning0
Effective ML Model Versioning in Edge Networks0
Effective Multimodal Reinforcement Learning with Modality Alignment and Importance Enhancement0
Effective reinforcement learning based local search for the maximum k-plex problem0
Effective Reinforcement Learning Based on Structural Information Principles0
Effective Scheduling Function Design in SDN through Deep Reinforcement Learning0
Effective sketching methods for value function approximation0
Effective Warm Start for the Online Actor-Critic Reinforcement Learning based mHealth Intervention0
Effects of a Social Force Model reward in Robot Navigation based on Deep Reinforcement Learning0
Effects of Conservatism on Offline Learning0
Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation0
Efficiency Separation between RL Methods: Model-Free, Model-Based and Goal-Conditioned0
Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty0
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning0
Efficient Adaptation of Reinforcement Learning Agents to Sudden Environmental Change0
Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning0
Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning0
Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion0
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search0
Efficient Bayesian Inverse Reinforcement Learning via Conditional Kernel Density Estimation0
Efficient Bayesian Policy Reuse with a Scalable Observation Model in Deep Reinforcement Learning0
Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning0
Efficient collective swimming by harnessing vortices through deep reinforcement learning0
Efficient Competitive Self-Play Policy Optimization0
Efficient Compressed Ratio Estimation Using Online Sequential Learning for Edge Computing0
Efficient Policy Generation in Multi-Agent Systems via Hypergraph Neural Network0
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Benchmark Results

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