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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 176–200 of 514 papers

TitleStatusHype
Evolutionary Reinforcement Learning via Cooperative Coevolution—0
An Offline Reinforcement Learning Algorithm Customized for Multi-Task Fusion in Large-Scale Recommender Systems—0
Sampling for Model Predictive Trajectory Planning in Autonomous Driving using Normalizing Flows—0
Learning Off-policy with Model-based Intrinsic Motivation For Active Online Exploration—0
Cognitive Planning for Object Goal Navigation using Generative AI Models—0
VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts—0
Safe Reinforcement Learning for Constrained Markov Decision Processes with Stochastic Stopping Time—0
Explore until Confident: Efficient Exploration for Embodied Question Answering—0
A Straightforward Gradient-Based Approach for High-Tc Superconductor Design: Leveraging Domain Knowledge via Adaptive Constraints—0
Hierarchical Spatial Proximity Reasoning for Vision-and-Language NavigationCode0
Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning—0
Scalable Online Exploration via CoverabilityCode0
Finding Waldo: Towards Efficient Exploration of NeRF Scene Spaces—0
A Natural Extension To Online Algorithms For Hybrid RL With Limited Coverage—0
Vlearn: Off-Policy Learning with Efficient State-Value Function Estimation—0
Noisy Spiking Actor Network for Exploration—0
ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularization—0
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank BanditsCode0
Diffusion Models Meet Contextual Bandits with Large Action Spaces—0
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian OptimizationCode0
TopoNav: Topological Navigation for Efficient Exploration in Sparse Reward Environments—0
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgentCode0
Efficient Exploration for LLMs—0
Scheduled Curiosity-Deep Dyna-Q: Efficient Exploration for Dialog Policy Learning—0
FIT-SLAM -- Fisher Information and Traversability estimation-based Active SLAM for exploration in 3D environments—0
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