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 12151–12200 of 15113 papers

TitleStatusHype
Towards an Adaptive Robot for Sports and Rehabilitation Coaching—0
Modeling Sensorimotor Coordination as Multi-Agent Reinforcement Learning with Differentiable Communication—0
Reinforcement Learning for Portfolio ManagementCode0
Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning—0
Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning—0
Joint Inference of Reward Machines and Policies for Reinforcement Learning—0
Correlation Priors for Reinforcement Learning—0
Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders—0
RecSim: A Configurable Simulation Platform for Recommender SystemsCode0
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning—0
Modelling Working Memory using Deep Recurrent Reinforcement Learning—0
Predicting optimal value functions by interpolating reward functions in scalarized multi-objective reinforcement learningCode0
On Memory Mechanism in Multi-Agent Reinforcement Learning—0
Transfer of Temporal Logic Formulas in Reinforcement Learning—0
Q-Learning Based Aerial Base Station Placement for Fairness Enhancement in Mobile Networks—0
Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning—0
MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning—0
Reinforcement Learning and Video Games—0
Sampling Strategies for GAN Synthetic Data—0
Discovery of Useful Questions as Auxiliary Tasks—0
Deep Reinforcement Learning Algorithm for Dynamic Pricing of Express Lanes with Multiple Access LocationsCode0
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning—0
A Survey on Reproducibility by Evaluating Deep Reinforcement Learning Algorithms on Real-World RobotsCode0
Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement LearningCode0
Exploratory Combinatorial Optimization with Reinforcement LearningCode0
AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal TeachersCode0
DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems—0
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning—0
Deterministic Value-Policy Gradients—0
Solving Continual Combinatorial Selection via Deep Reinforcement Learning—0
Recommendation System-based Upper Confidence Bound for Online Advertising—0
Off-Policy Evaluation in Partially Observable Environments—0
Partner Approximating Learners (PAL): Simulation-Accelerated Learning with Explicit Partner Modeling in Multi-Agent Domains—0
Neural Architecture Search in Embedding Space—0
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning—0
Self-driving scale car trained by Deep reinforcement learning—0
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity—0
Imitation Learning for Human Pose Prediction—0
Deep Reinforcement Learning for Control of Probabilistic Boolean NetworksCode0
Automatic Financial Trading Agent for Low-risk Portfolio Management using Deep Reinforcement Learning—0
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement LearningCode0
Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning—0
Gradient Q(σ, λ): A Unified Algorithm with Function Approximation for Reinforcement Learning—0
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information—0
DRLViz: Understanding Decisions and Memory in Deep Reinforcement LearningCode0
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based ControlCode0
Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation—0
Reinforcement Learning for Joint Optimization of Multiple Rewards—0
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs—0
Classification with Costly Features as a Sequential Decision-Making ProblemCode0
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Benchmark Results

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