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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 451–500 of 514 papers

TitleStatusHype
Exploration by Uncertainty in Reward Space—0
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain—0
Exploration in Model-based Reinforcement Learning with Randomized Reward—0
Exploration of the search space of Gaussian graphical models for paired data—0
Exploration via Epistemic Value Estimation—0
Exploratory Diffusion Model for Unsupervised Reinforcement Learning—0
Explore until Confident: Efficient Exploration for Embodied Question Answering—0
Exploring More When It Needs in Deep Reinforcement Learning—0
Cognitive Planning for Object Goal Navigation using Generative AI Models—0
Extended Formulations for Online Linear Bandit Optimization—0
FALCONEye: Finding Answers and Localizing Content in ONE-hour-long videos with multi-modal LLMs—0
Fast exploration and learning of latent graphs with aliased observations—0
Feature and Instance Joint Selection: A Reinforcement Learning Perspective—0
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
Finding Waldo: Towards Efficient Exploration of NeRF Scene Spaces—0
Finedeep: Mitigating Sparse Activation in Dense LLMs via Multi-Layer Fine-Grained Experts—0
FIT-SLAM -- Fisher Information and Traversability estimation-based Active SLAM for exploration in 3D environments—0
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences—0
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for MCMC—0
Fractional Langevin Monte Carlo: Exploring Lévy Driven Stochastic Differential Equations for Markov Chain Monte Carlo—0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making—0
From proprioception to long-horizon planning in novel environments: A hierarchical RL model—0
GAN-based Intrinsic Exploration For Sample Efficient Reinforcement Learning—0
GFlowNets for AI-Driven Scientific Discovery—0
GLaD: Synergizing Molecular Graphs and Language Descriptors for Enhanced Power Conversion Efficiency Prediction in Organic Photovoltaic Devices—0
Goal-oriented Trajectories for Efficient Exploration—0
Go-Browse: Training Web Agents with Structured Exploration—0
Go-Explore for Residential Energy Management—0
GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering—0
Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion—0
Guarded Policy Optimization with Imperfect Online Demonstrations—0
Guided Exploration for Efficient Relational Model Learning—0
Hands-Free Segmentation of Medical Volumes via Binary Inputs—0
Hashing over Predicted Future Frames for Informed Exploration of Deep Reinforcement Learning—0
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression—0
HelixDesign-Binder: A Scalable Production-Grade Platform for Binder Design Built on HelixFold3—0
Hierarchical reinforcement learning for efficient exploration and transfer—0
HyperArm Bandit Optimization: A Novel approach to Hyperparameter Optimization and an Analysis of Bandit Algorithms in Stochastic and Adversarial Settings—0
Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning—0
IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions—0
Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks—0
Impact of detecting clinical trial elements in exploration of COVID-19 literature—0
Implicit Generative Modeling for Efficient Exploration—0
Improving a State-of-the-Art Heuristic for the Minimum Latency Problem with Data Mining—0
Incentivizing Exploration with Selective Data Disclosure—0
Inferring Hierarchical Structure in Multi-Room Maze Environments—0
Information Content Exploration—0
Interpretable SHAP-bounded Bayesian Optimization for Underwater Acoustic Metamaterial Coating Design—0
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search—0
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