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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 201–225 of 514 papers

TitleStatusHype
Directed Exploration for Reinforcement Learning—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
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
Deterministic Sequencing of Exploration and Exploitation for Reinforcement Learning—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
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
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
Finedeep: Mitigating Sparse Activation in Dense LLMs via Multi-Layer Fine-Grained Experts—0
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