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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

Showing 6170 of 514 papers

TitleStatusHype
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?Code1
GeoThermalCloud: Machine Learning for Geothermal Resource ExplorationCode1
SC-Explorer: Incremental 3D Scene Completion for Safe and Efficient Exploration Mapping and PlanningCode1
Learning Dexterous Manipulation from Exemplar Object Trajectories and Pre-GraspsCode1
Meta Reinforcement Learning with Autonomous Inference of Subtask DependenciesCode1
Generative Colorization of Structured Mobile Web PagesCode1
Adversarially Guided Actor-CriticCode1
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic EnvironmentsCode1
BPP-Search: Enhancing Tree of Thought Reasoning for Mathematical Modeling Problem SolvingCode0
Adaptive teachers for amortized samplersCode0
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