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Efficient Exploration

Efficient Exploration is one of the main obstacles in scaling up modern deep reinforcement learning algorithms. The main challenge in Efficient Exploration is the balance between exploiting current estimates, and gaining information about poorly understood states and actions.

Source: Randomized Value Functions via Multiplicative Normalizing Flows

Papers

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Showing 1–25 of 514 papers

TitleStatusHype
MOORL: A Framework for Integrating Offline-Online Reinforcement Learning—0
Go-Browse: Training Web Agents with Structured Exploration—0
DrSR: LLM based Scientific Equation Discovery with Dual Reasoning from Data and Experience—0
WoMAP: World Models For Embodied Open-Vocabulary Object Localization—0
MermaidFlow: Redefining Agentic Workflow Generation via Safety-Constrained Evolutionary ProgrammingCode2
HelixDesign-Binder: A Scalable Production-Grade Platform for Binder Design Built on HelixFold3—0
DISCOVER: Automated Curricula for Sparse-Reward Reinforcement LearningCode0
STAR-R1: Spacial TrAnsformation Reasoning by Reinforcing Multimodal LLMsCode0
Comparative Analysis of Black-Box Optimization Methods for Weather Intervention Design—0
IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-TuningCode0
Distilling Realizable Students from Unrealizable Teachers—0
Language Agents Mirror Human Causal Reasoning Biases. How Can We Help Them Think Like Scientists?—0
Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning—0
Interpretable SHAP-bounded Bayesian Optimization for Underwater Acoustic Metamaterial Coating Design—0
An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm—0
ForesightNav: Learning Scene Imagination for Efficient ExplorationCode2
Aerial Active STAR-RIS-assisted Satellite-Terrestrial Covert Communications—0
Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training—0
Memetic Search for Green Vehicle Routing Problem with Private Capacitated Refueling Stations—0
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making—0
Entropy-guided sequence weighting for efficient exploration in RL-based LLM fine-tuning—0
Maya: Optimizing Deep Learning Training Workloads using Emulated Virtual Accelerators—0
FALCONEye: Finding Answers and Localizing Content in ONE-hour-long videos with multi-modal LLMs—0
CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning—0
KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies—0
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