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 8501–8525 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning for Wireless Resource Allocation Using Buffer State Information—0
WAD: A Deep Reinforcement Learning Agent for Urban Autonomous Driving—0
When should agents explore?—0
Model-based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian—0
Robust Model-based Reinforcement Learning for Autonomous Greenhouse Control—0
Deep Reinforcement Learning for Dynamic Band Switch in Cellular-Connected UAV—0
Adaptive Control of Differentially Private Linear Quadratic Systems—0
Federated Reinforcement Learning: Techniques, Applications, and Open Challenges—0
Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey—0
Adversary agent reinforcement learning for pursuit-evasion—0
Entropy-Aware Model Initialization for Effective Exploration in Deep Reinforcement Learning—0
Self-optimizing adaptive optics control with Reinforcement Learning for high-contrast imaging—0
No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees—0
Power Grid Cascading Failure Mitigation by Reinforcement Learning—0
Collect & Infer -- a fresh look at data-efficient Reinforcement Learning—0
A Boosting Approach to Reinforcement Learning—0
MimicBot: Combining Imitation and Reinforcement Learning to win in Bot Bowl—0
Reinforcement Learning to Optimize Lifetime Value in Cold-Start Recommendation—0
Plug and Play, Model-Based Reinforcement Learning—0
An Independent Study of Reinforcement Learning and Autonomous Driving—0
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey—0
Crown Jewels Analysis using Reinforcement Learning with Attack Graphs—0
Cooperative Localization Utilizing Reinforcement Learning for 5G Networks—0
Global Convergence of the ODE Limit for Online Actor-Critic Algorithms in Reinforcement Learning—0
A Reinforcement Learning Approach for GNSS Spoofing Attack Detection of Autonomous Vehicles—0
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Benchmark Results

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