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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 201–250 of 514 papers

TitleStatusHype
Improving a State-of-the-Art Heuristic for the Minimum Latency Problem with Data Mining—0
Deep density networks and uncertainty in recommender systems—0
Co-NavGPT: Multi-Robot Cooperative Visual Semantic Navigation Using Vision Language Models—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
Deep exploration by novelty-pursuit with maximum state entropy—0
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
Efficient exploration of zero-sum stochastic games—0
Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks—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
DEEPGONET: Multi-label Prediction of GO Annotation for Protein from Sequence Using Cascaded Convolutional and Recurrent Network—0
FIT-SLAM -- Fisher Information and Traversability estimation-based Active SLAM for exploration in 3D environments—0
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization—0
ActiveGAMER: Active GAussian Mapping through Efficient Rendering—0
Impact of detecting clinical trial elements in exploration of COVID-19 literature—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
Incentivizing Exploration with Selective Data Disclosure—0
Efficient Exploration of Image Classifier Failures with Bayesian Optimization and Text-to-Image Models—0
A Straightforward Gradient-Based Approach for High-Tc Superconductor Design: Leveraging Domain Knowledge via Adaptive Constraints—0
Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach—0
Efficient Exploration of Gradient Space for Online Learning to Rank—0
Efficient Exploration in Resource-Restricted Reinforcement Learning—0
Computational Discovery of Microstructured Composites with Optimal Stiffness-Toughness Trade-Offs—0
GLaD: Synergizing Molecular Graphs and Language Descriptors for Enhanced Power Conversion Efficiency Prediction in Organic Photovoltaic Devices—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
Auto-MAP: A DQN Framework for Exploring Distributed Execution Plans for DNN Workloads—0
Goal-oriented Trajectories for Efficient Exploration—0
Diffusion Models Meet Contextual Bandits with Large Action Spaces—0
Efficient Exploration in Deep Reinforcement Learning: A Novel Bayesian Actor-Critic Algorithm—0
Efficient Exploration in Continuous-time Model-based Reinforcement Learning—0
Go-Explore for Residential Energy Management—0
GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering—0
Comprehensive decision-strategy space exploration for efficient territorial planning strategies—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
KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance—0
Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path—0
Efficient Exploration in Binary and Preferential Bayesian Optimization—0
A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search—0
Aerial Active STAR-RIS-assisted Satellite-Terrestrial Covert Communications—0
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