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

Showing 45014550 of 15113 papers

TitleStatusHype
AlgaeDICE: Policy Gradient from Arbitrary Experience0
AlgoPilot: Fully Autonomous Program Synthesis Without Human-Written Programs0
Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning0
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction0
Algorithmic Prompt Generation for Diverse Human-like Teaming and Communication with Large Language Models0
Algorithmic Trading Using Continuous Action Space Deep Reinforcement Learning0
Algorithms for Batch Hierarchical Reinforcement Learning0
Algorithms for Learning Markov Field Policies0
Algorithms in Multi-Agent Systems: A Holistic Perspective from Reinforcement Learning and Game Theory0
A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning0
A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN0
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model0
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback0
Aligning Humans and Robots via Reinforcement Learning from Implicit Human Feedback0
Aligning Language Models with Offline Learning from Human Feedback0
Alignment and Safety of Diffusion Models via Reinforcement Learning and Reward Modeling: A Survey0
Align Your Intents: Offline Imitation Learning via Optimal Transport0
All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning0
Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition0
Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition0
A Local Temporal Difference Code for Distributional Reinforcement Learning0
A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning0
AlphaD3M: Machine Learning Pipeline Synthesis0
Alpha-DAG: a reinforcement learning based algorithm to learn Directed Acyclic Graphs0
Alpha-divergence bridges maximum likelihood and reinforcement learning in neural sequence generation0
AlphaRouter: Quantum Circuit Routing with Reinforcement Learning and Tree Search0
AlphaSeq: Sequence Discovery with Deep Reinforcement Learning0
AlphaSnake: Policy Iteration on a Nondeterministic NP-hard Markov Decision Process0
AlphaStar: An Evolutionary Computation Perspective0
AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks0
Alternating Good-for-MDP Automata0
Alternative Function Approximation Parameterizations for Solving Games: An Analysis of f-Regression Counterfactual Regret Minimization0
AltGraph: Redesigning Quantum Circuits Using Generative Graph Models for Efficient Optimization0
A Lyapunov Drift-Plus-Penalty Method Tailored for Reinforcement Learning with Queue Stability0
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants0
A Machine Learning Approach for Prosumer Management in Intraday Electricity Markets0
A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks0
A Machine Learning Approach to Routing0
A Machine of Few Words -- Interactive Speaker Recognition with Reinforcement Learning0
A Maintenance Planning Framework using Online and Offline Deep Reinforcement Learning0
Ambiguous Dynamic Treatment Regimes: A Reinforcement Learning Approach0
A Memetic Algorithm with Reinforcement Learning for Sociotechnical Production Scheduling0
A Memory-Based Reinforcement Learning Approach to Integrated Sensing and Communication0
A Memory Efficient Deep Reinforcement Learning Approach For Snake Game Autonomous Agents0
Task-Agnostic Learning to Accomplish New Tasks0
A Meta-Reinforcement Learning Approach to Process Control0
A Method for Fast Autonomy Transfer in Reinforcement Learning0
A method for the online construction of the set of states of a Markov Decision Process using Answer Set Programming0
A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers0
A Microscopic Pandemic Simulator for Pandemic Prediction Using Scalable Million-Agent Reinforcement Learning0
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Benchmark Results

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