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 8551–8600 of 15113 papers

TitleStatusHype
Integrating process design and control using reinforcement learning—0
Low-level Pose Control of Tilting Multirotor for Wall Perching Tasks Using Reinforcement Learning—0
An Approach to Partial Observability in Games: Learning to Both Act and Observe—0
Does Explicit Prediction Matter in Deep Reinforcement Learning-Based Energy Management?—0
Fairness Through Counterfactual UtilitiesCode0
Gap-Dependent Unsupervised Exploration for Reinforcement LearningCode0
Truncated Emphatic Temporal Difference Methods for Prediction and Control—0
Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey—0
Imitation Learning by Reinforcement LearningCode0
High Quality Related Search Query Suggestions using Deep Reinforcement Learning—0
A Survey on Deep Reinforcement Learning for Data Processing and Analytics—0
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs—0
Knowledge accumulating: The general pattern of learning—0
Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning—0
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization—0
Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning—0
Meta-Reinforcement Learning in Broad and Non-Parametric EnvironmentsCode0
Learning Proxemic Behavior Using Reinforcement Learning with Cognitive Agents—0
Efficient Representation for Electric Vehicle Charging Station Operations using Reinforcement Learning—0
A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning—0
Deep Reinforcement Learning for Intelligent Reflecting Surface-assisted D2D Communications—0
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning—0
On the Robustness of Controlled Deep Reinforcement Learning for Slice Placement—0
Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach—0
Responding to Illegal Activities Along the Canadian Coastlines Using Reinforcement Learning—0
Reinforcement Learning for Intelligent Healthcare Systems: A Comprehensive Survey—0
Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty—0
Online Model-Free Reinforcement Learning for the Automatic Control of a Flexible Wing Aircraft—0
RIS-assisted UAV Communications for IoT with Wireless Power Transfer Using Deep Reinforcement Learning—0
Distilling Neuron Spike with High Temperature in Reinforcement Learning Agents—0
Active Reinforcement Learning over MDPs—0
Ensemble Consensus-based Representation Deep Reinforcement Learning for Hybrid FSO/RF Communication Systems—0
DRL-based Slice Placement Under Non-Stationary Conditions—0
Beyond No Regret: Instance-Dependent PAC Reinforcement Learning—0
Deep Reinforcement Learning for Continuous Docking Control of Autonomous Underwater Vehicles: A Benchmarking Study—0
An Elementary Proof that Q-learning Converges Almost Surely—0
Learning Task Agnostic Skills with Data-driven GuidanceCode0
Parallelized Reverse Curriculum Generation—0
Policy Gradients Incorporating the Future—0
Offline Decentralized Multi-Agent Reinforcement Learning—0
Optimal Management of the Peak Power Penalty for Smart Grids Using MPC-based Reinforcement Learning—0
Deep Reinforcement Learning Based Networked Control with Network Delays for Signal Temporal Logic Specifications—0
Controlled Deep Reinforcement Learning for Optimized Slice Placement—0
Accelerating the Learning of TAMER with Counterfactual Explanations—0
Factor Representation and Decision Making in Stock Markets Using Deep Reinforcement Learning—0
Adversarial Attacks Against Deep Reinforcement Learning Framework in Internet of Vehicles—0
Interactive Reinforcement Learning for Table Balancing Robot—0
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC—0
Language-based General Action Template for Reinforcement Learning Agents—0
A Reinforcement Learning Approach for Scheduling in mmWave Networks—0
Show:102550
← PrevPage 172 of 303Next →

Benchmark Results

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