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 951–1000 of 15113 papers

TitleStatusHype
SUBER: An RL Environment with Simulated Human Behavior for Recommender SystemsCode1
Hierarchical Kickstarting for Skill Transfer in Reinforcement LearningCode1
Hierarchical Reinforcement Learning By Discovering Intrinsic OptionsCode1
Hierarchical Reinforcement Learning for Power Network Topology ControlCode1
An Application of Deep Reinforcement Learning to Algorithmic TradingCode1
Constrained Update Projection Approach to Safe Policy OptimizationCode1
HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent PathfindingCode1
A Modular Framework for Reinforcement Learning Optimal ExecutionCode1
A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric VehiclesCode1
Hoplite: Efficient and Fault-Tolerant Collective Communication for Task-Based Distributed SystemsCode1
How Consistent are Clinicians? Evaluating the Predictability of Sepsis Disease Progression with Dynamics ModelsCode1
Constructions in combinatorics via neural networksCode1
Contextualized Rewriting for Text SummarizationCode1
Contrastive Preference Learning: Learning from Human Feedback without RLCode1
Critic-Guided Decision Transformer for Offline Reinforcement LearningCode1
Human-Level Control through Directly-Trained Deep Spiking Q-NetworksCode1
Hybrid Inverse Reinforcement LearningCode1
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand SystemsCode1
HyperDQN: A Randomized Exploration Method for Deep Reinforcement LearningCode1
HyperNCA: Growing Developmental Networks with Neural Cellular AutomataCode1
ICU-Sepsis: A Benchmark MDP Built from Real Medical DataCode1
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement LearningCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal ControlCode1
Imitating Graph-Based Planning with Goal-Conditioned PoliciesCode1
Discriminator-Weighted Offline Imitation Learning from Suboptimal DemonstrationsCode1
Imitation Learning via Off-Policy Distribution MatchingCode1
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner ArchitecturesCode1
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICsCode1
Implicit Distributional Reinforcement LearningCode1
Implicit Unlikelihood Training: Improving Neural Text Generation with Reinforcement LearningCode1
A Multiplicative Value Function for Safe and Efficient Reinforcement LearningCode1
ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial MarketsCode1
Improving Computational Efficiency in Visual Reinforcement Learning via Stored EmbeddingsCode1
An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agentsCode1
Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics MixtureCode1
Improving Model-Based Reinforcement Learning with Internal State Representations through Self-SupervisionCode1
Conservative Offline Distributional Reinforcement LearningCode1
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Code1
Goal-directed graph construction using reinforcement learningCode1
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement LearningCode1
An Open-Source Multi-Goal Reinforcement Learning Environment for Robotic Manipulation with PybulletCode1
In Defense of the Unitary Scalarization for Deep Multi-Task LearningCode1
Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control ProblemCode1
Conservative Q-Learning for Offline Reinforcement LearningCode1
Information Directed Reward Learning for Reinforcement LearningCode1
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive SummarizationCode1
Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving IntelligenceCode1
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement LearningCode1
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Benchmark Results

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