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 9926–9950 of 15113 papers

TitleStatusHype
Bayesian Inverse Reinforcement Learning for Collective Animal MovementCode0
Induction and Exploitation of Subgoal Automata for Reinforcement Learning—0
Deep Active Inference for Partially Observable MDPsCode1
Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search—0
Energy Expenditure Estimation Through Daily Activity Recognition Using a Smart-phone—0
Graph neural networks-based Scheduler for Production planning problems using Reinforcement Learning—0
Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning—0
Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment—0
Driving Tasks Transfer in Deep Reinforcement Learning for Decision-making of Autonomous Vehicles—0
Active Learning of Causal Structures with Deep Reinforcement Learning—0
Robust Spoken Language Understanding with RL-based Value Error Recovery—0
PAC Reinforcement Learning Algorithm for General-Sum Markov Games—0
A Hybrid PAC Reinforcement Learning Algorithm—0
Visualizing the Loss Landscape of Actor Critic Methods with Applications in Inventory Optimization—0
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement LearningCode1
DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoVCode2
Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement LearningCode0
Sparse Meta Networks for Sequential Adaptation and its Application to Adaptive Language Modelling—0
Sample-Efficient Automated Deep Reinforcement LearningCode1
TAP-Net: Transport-and-Pack using Reinforcement Learning—0
Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises—0
A reinforcement learning approach to hybrid control design—0
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics—0
PlotThread: Creating Expressive Storyline Visualizations using Reinforcement Learning—0
Solving the single-track train scheduling problem via Deep Reinforcement Learning—0
Show:102550
← PrevPage 398 of 605Next →

Benchmark Results

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