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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 1–50 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
Language Agents Mirror Human Causal Reasoning Biases. How Can We Help Them Think Like Scientists?—0
Distilling Realizable Students from Unrealizable Teachers—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
Disentangling Uncertainties by Learning Compressed Data RepresentationCode0
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model—0
HyperArm Bandit Optimization: A Novel approach to Hyperparameter Optimization and an Analysis of Bandit Algorithms in Stochastic and Adversarial Settings—0
Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration—0
Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty EnvironmentsCode0
Probabilistic Insights for Efficient Exploration Strategies in Reinforcement Learning—0
A Transformer Model for Predicting Chemical Reaction Products from Generic Templates—0
Contextualizing biological perturbation experiments through languageCode1
Training a Generally Curious AgentCode1
On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach—0
Synergistic Fusion of Multi-Source Knowledge via Evidence Theory for High-Entropy Alloy Discovery—0
Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation—0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models—0
Finedeep: Mitigating Sparse Activation in Dense LLMs via Multi-Layer Fine-Grained Experts—0
Maximum Entropy Reinforcement Learning with Diffusion PolicyCode1
Massively Scaling Explicit Policy-conditioned Value Functions—0
Causal Information Prioritization for Efficient Reinforcement Learning—0
Exploratory Diffusion Model for Unsupervised Reinforcement Learning—0
Guided Exploration for Efficient Relational Model Learning—0
Few-shot_LLM_Synthetic_Data_with_Distribution_MatchingCode0
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation—0
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic EnvironmentsCode1
Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic LearningCode1
Constrained Hybrid Metaheuristic Algorithm for Probabilistic Neural Networks Learning—0
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