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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 51–75 of 514 papers

TitleStatusHype
Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid LocomotionCode1
Evolutionary Large Language Model for Automated Feature TransformationCode1
BeBold: Exploration Beyond the Boundary of Explored RegionsCode1
Scaling MAP-Elites to Deep NeuroevolutionCode1
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic EnvironmentsCode1
State Entropy Maximization with Random Encoders for Efficient ExplorationCode1
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?Code1
Hierarchical Skills for Efficient ExplorationCode1
Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic LearningCode1
Tuning Legged Locomotion Controllers via Safe Bayesian OptimizationCode1
MetaCURE: Meta Reinforcement Learning with Empowerment-Driven ExplorationCode1
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep NetworksCode1
Optimistic Exploration even with a Pessimistic InitialisationCode1
Diffusion-Reinforcement Learning Hierarchical Motion Planning in Multi-agent Adversarial GamesCode1
A Survey of Label-Efficient Deep Learning for 3D Point CloudsCode1
GeoThermalCloud: Machine Learning for Geothermal Resource ExplorationCode1
Adversarially Guided Actor-CriticCode1
Contextualizing biological perturbation experiments through languageCode1
BPP-Search: Enhancing Tree of Thought Reasoning for Mathematical Modeling Problem SolvingCode0
Adaptive teachers for amortized samplersCode0
Bootstrapped Meta-LearningCode0
ASCENT: Amplifying Power Side-Channel Resilience via Learning & Monte-Carlo Tree SearchCode0
Fire Burns, Sword Cuts: Commonsense Inductive Bias for Exploration in Text-based GamesCode0
Generalization and Exploration via Randomized Value FunctionsCode0
Feature Interaction Aware Automated Data Representation TransformationCode0
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