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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
DISCO-10M: A Large-Scale Music Dataset—0
Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion—0
Directed Exploration in PAC Model-Free Reinforcement Learning—0
Biased Estimates of Advantages over Path Ensembles—0
A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning—0
Directed Exploration for Reinforcement Learning—0
Go-Browse: Training Web Agents with Structured Exploration—0
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning—0
Diffusion Models Meet Contextual Bandits with Large Action Spaces—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
Beyond Games: Bringing Exploration to Robots in Real-world—0
Approximate information for efficient exploration-exploitation strategies—0
GFlowNets for AI-Driven Scientific Discovery—0
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning—0
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models—0
Differentially Evolving Memory Ensembles: Pareto Optimization based on Computational Intelligence for Embedded Memories on a System Level—0
Better Exploration with Optimistic Actor-Critic—0
An Offline Reinforcement Learning Algorithm Customized for Multi-Task Fusion in Large-Scale Recommender Systems—0
A Compression-Inspired Framework for Macro Discovery—0
GAN-based Intrinsic Exploration For Sample Efficient Reinforcement Learning—0
From proprioception to long-horizon planning in novel environments: A hierarchical RL model—0
Deterministic Sequencing of Exploration and Exploitation for Reinforcement Learning—0
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making—0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
Design of Convolutional Extreme Learning Machines for Vision-Based Navigation Around Small Bodies—0
Fractional Langevin Monte Carlo: Exploring Lévy Driven Stochastic Differential Equations for Markov Chain Monte Carlo—0
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for MCMC—0
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences—0
Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching—0
GLaD: Synergizing Molecular Graphs and Language Descriptors for Enhanced Power Conversion Efficiency Prediction in Organic Photovoltaic Devices—0
FIT-SLAM -- Fisher Information and Traversability estimation-based Active SLAM for exploration in 3D environments—0
DEEPGONET: Multi-label Prediction of GO Annotation for Protein from Sequence Using Cascaded Convolutional and Recurrent Network—0
Goal-oriented Trajectories for Efficient Exploration—0
Finedeep: Mitigating Sparse Activation in Dense LLMs via Multi-Layer Fine-Grained Experts—0
Finding Waldo: Towards Efficient Exploration of NeRF Scene Spaces—0
Deep Exploration via Randomized Value Functions—0
Go-Explore for Residential Energy Management—0
GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering—0
β-DQN: Improving Deep Q-Learning By Evolving the Behavior—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
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
Deep exploration by novelty-pursuit with maximum state entropy—0
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems—0
An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm—0
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation—0
Feature and Instance Joint Selection: A Reinforcement Learning Perspective—0
Fast exploration and learning of latent graphs with aliased observations—0
FALCONEye: Finding Answers and Localizing Content in ONE-hour-long videos with multi-modal LLMs—0
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