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

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Showing 8151–8200 of 15113 papers

TitleStatusHype
Goal Misgeneralization in Deep Reinforcement LearningCode1
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model—0
Risk-Aware Transfer in Reinforcement Learning using Successor Features—0
Optimistic Reinforcement Learning by Forward Kullback-Leibler Divergence Optimization—0
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching—0
Branching Dueling Q-Network Based Online Scheduling of a Microgrid With Distributed Energy Storage Systems—0
AndroidEnv: A Reinforcement Learning Platform for AndroidCode2
A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem—0
Adversarial Intrinsic Motivation for Reinforcement LearningCode0
Context-aware taxi dispatching at city-scale using deep reinforcement learning—0
Successive Convex Approximation Based Off-Policy Optimization for Constrained Reinforcement LearningCode0
Trajectory Modeling via Random Utility Inverse Reinforcement Learning—0
Unbiased Asymmetric Reinforcement Learning under Partial Observability—0
Safe Model-based Off-policy Reinforcement Learning for Eco-Driving in Connected and Automated Hybrid Electric Vehicles—0
Robust Value Iteration for Continuous Control TasksCode1
Towards Scalable Verification of Deep Reinforcement LearningCode0
Transfer Learning and Curriculum Learning in Sokoban—0
A Generalised Inverse Reinforcement Learning Framework—0
A Comparison of Reward Functions in Q-Learning Applied to a Cart Position ProblemCode0
Bayesian Nonparametric Reinforcement Learning in LTE and Wi-Fi Coexistence—0
KnowSR: Knowledge Sharing among Homogeneous Agents in Multi-agent Reinforcement Learning—0
Interpretable UAV Collision Avoidance using Deep Reinforcement Learning—0
IGO-QNN: Quantum Neural Network Architecture for Inductive Grover Oracularization—0
FNAS: Uncertainty-Aware Fast Neural Architecture Search—0
Verification of Dissipativity and Evaluation of Storage Function in Economic Nonlinear MPC using Q-Learning—0
Room Clearance with Feudal Hierarchical Reinforcement Learning—0
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence—0
An Efficient Application of Neuroevolution for Competitive Multiagent LearningCode0
Continual World: A Robotic Benchmark For Continual Reinforcement LearningCode1
Attention-based Reinforcement Learning for Real-Time UAV Semantic Communication—0
Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise SafetyCode1
Stochastic Approximation of Gaussian Free Energy for Risk-Sensitive Reinforcement Learning—0
Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection StrategiesCode1
Meta Reinforcement Learning for Fast Adaptation of Hierarchical Policies—0
Reinforcement learning for instance segmentation with high-level priors—0
Reinforcement Learning based Disease Progression Model for Alzheimer’s Disease—0
Revisiting Design Choices in Offline Model Based Reinforcement Learning—0
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap—0
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning—0
Gym-μRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement LearningCode1
Certification of Iterative Predictions in Bayesian Neural NetworksCode0
De-Biased Modelling of Search Click Behavior with Reinforcement Learning—0
Ensemble Quantile Networks: Uncertainty-Aware Reinforcement Learning with Applications in Autonomous DrivingCode1
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games—0
Techniques Toward Optimizing Viewability in RTB Ad Campaigns Using Reinforcement Learning—0
Rule Augmented Unsupervised Constituency ParsingCode0
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search—0
On the use of feature-maps and parameter control for improved quality-diversity meta-evolution—0
On Instrumental Variable Regression for Deep Offline Policy EvaluationCode0
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Benchmark Results

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