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 1451–1500 of 15113 papers

TitleStatusHype
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner ArchitecturesCode1
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPOCode1
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICsCode1
Implicit Distributional Reinforcement LearningCode1
Accelerating Reinforcement Learning with Learned Skill PriorsCode1
Improving and Benchmarking Offline Reinforcement Learning AlgorithmsCode1
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout ReplayCode1
Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics MixtureCode1
Improving Model-Based Reinforcement Learning with Internal State Representations through Self-SupervisionCode1
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMsCode1
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Code1
Goal-directed graph construction using reinforcement learningCode1
Actor-Critic Reinforcement Learning for Control with Stability GuaranteeCode1
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-ThoughtCode1
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learningCode1
In Defense of the Unitary Scalarization for Deep Multi-Task LearningCode1
A Game-Theoretic Approach to Multi-Agent Trust Region OptimizationCode1
A simple but strong baseline for online continual learning: Repeated Augmented RehearsalCode1
CommonPower: A Framework for Safe Data-Driven Smart Grid ControlCode1
Information Directed Reward Learning for Reinforcement LearningCode1
Comparing Popular Simulation Environments in the Scope of Robotics and Reinforcement LearningCode1
Concise Reasoning via Reinforcement LearningCode1
Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning ApproachCode1
Intention-Conditioned Flow Occupancy ModelsCode1
Consistency Models as a Rich and Efficient Policy Class for Reinforcement LearningCode1
Interactive Machine Learning of Musical GestureCode1
Interferobot: aligning an optical interferometer by a reinforcement learning agentCode1
Learning to combine primitive skills: A step towards versatile robotic manipulationCode1
Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning ApproachCode1
A Text-based Deep Reinforcement Learning Framework for Interactive RecommendationCode1
A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing ProblemsCode1
Intrinsic Reward Driven Imitation Learning via Generative ModelCode1
A General Contextualized Rewriting Framework for Text SummarizationCode1
Inverse Constrained Reinforcement LearningCode1
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement LearningCode1
Investigating practical linear temporal difference learningCode1
Combining Modular Skills in Multitask LearningCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
A Deep Reinforced Model for Zero-Shot Cross-Lingual Summarization with Bilingual Semantic Similarity RewardsCode1
Combining Deep Reinforcement Learning and Search for Imperfect-Information GamesCode1
Aspect Sentiment Triplet Extraction Using Reinforcement LearningCode1
JoinGym: An Efficient Query Optimization Environment for Reinforcement LearningCode1
Combining Reinforcement Learning and Constraint Programming for Combinatorial OptimizationCode1
Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley ValuesCode1
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning StudyCode1
Karolos: An Open-Source Reinforcement Learning Framework for Robot-Task EnvironmentsCode1
A Deep Reinforced Model for Abstractive SummarizationCode1
Collision Probability Distribution Estimation via Temporal Difference LearningCode1
Knowledge-guided Open Attribute Value Extraction with Reinforcement LearningCode1
Collaborative Multi-Agent Dialogue Model Training Via Reinforcement LearningCode1
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Benchmark Results

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