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 7601–7650 of 15113 papers

TitleStatusHype
Modified DDPG car-following model with a real-world human driving experience with CARLA simulator—0
Control Theoretic Analysis of Temporal Difference Learning—0
Sequential memory improves sample and memory efficiency in Episodic ControlCode0
Robustness and risk management via distributional dynamic programming—0
Exponential Family Model-Based Reinforcement Learning via Score MatchingCode0
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations—0
Embodied Learning for Lifelong Visual Perception—0
Improving the Performance of Backward Chained Behavior Trees that use Reinforcement LearningCode0
Intelligent Traffic Light via Policy-based Deep Reinforcement LearningCode0
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers?—0
Multiagent Model-based Credit Assignment for Continuous Control—0
A Graph Attention Learning Approach to Antenna Tilt Optimization—0
Safe Reinforcement Learning with Chance-constrained Model Predictive Control—0
The Statistical Complexity of Interactive Decision Making—0
RELDEC: Reinforcement Learning-Based Decoding of Moderate Length LDPC Codes—0
Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions—0
Neuro-Symbolic Hierarchical Rule Induction—0
Abstractions of General Reinforcement Learning—0
A Survey on Interpretable Reinforcement Learning—0
Dynamic Channel Access via Meta-Reinforcement Learning—0
An Efficient Combinatorial Optimization Model Using Learning-to-Rank DistillationCode0
On the Unreasonable Efficiency of State Space Clustering in Personalization TasksCode0
Rediscovering Affordance: A Reinforcement Learning Perspective—0
Missing Velocity in Dynamic Obstacle Avoidance based on Deep Reinforcement Learning—0
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning—0
Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions—0
Deep Reinforcement Learning for Optimal Power Flow with Renewables Using Graph Information—0
Graph augmented Deep Reinforcement Learning in the GameRLand3D environment—0
Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving EnvironmentCode0
Alpha-Mini: Minichess Agent with Deep Reinforcement LearningCode0
Newsvendor Model with Deep Reinforcement LearningCode0
Off Environment Evaluation Using Convex Risk MinimizationCode0
Soft Actor-Critic with Cross-Entropy Policy OptimizationCode0
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee—0
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design—0
Aerial Base Station Positioning and Power Control for Securing Communications: A Deep Q-Network Approach—0
District Cooling System Control for Providing Operating Reserve based on Safe Deep Reinforcement Learning—0
A Scalable Deep Reinforcement Learning Model for Online Scheduling Coflows of Multi-Stage Jobs for High Performance Computing—0
Do Androids Dream of Electric Fences? Safety-Aware Reinforcement Learning with Latent Shielding—0
A deep reinforcement learning model for predictive maintenance planning of road assets: Integrating LCA and LCCA—0
AGPNet -- Autonomous Grading Policy Network—0
Differentially Private Regret Minimization in Episodic Markov Decision ProcessesCode0
Interpretable Preference-based Reinforcement Learning with Tree-Structured Reward Functions—0
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units—0
CGIBNet: Bandwidth-constrained Communication with Graph Information Bottleneck in Multi-Agent Reinforcement Learning—0
RoboAssembly: Learning Generalizable Furniture Assembly Policy in a Novel Multi-robot Contact-rich Simulation Environment—0
Masked Deep Q-Recommender for Effective Question Scheduling—0
Exploration-exploitation trade-off for continuous-time episodic reinforcement learning with linear-convex models—0
Creativity of AI: Hierarchical Planning Model Learning for Facilitating Deep Reinforcement Learning—0
Curriculum Based Reinforcement Learning of Grid Topology Controllers to Prevent Thermal Cascading—0
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Benchmark Results

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