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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 76–100 of 514 papers

TitleStatusHype
TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement LearningCode0
Meta-Learning Integration in Hierarchical Reinforcement Learning for Advanced Task ComplexityCode0
Latent Action Priors for Locomotion with Deep Reinforcement Learning—0
BayesCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale—0
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical ReasoningCode5
Adaptive teachers for amortized samplersCode0
Provably Efficient Exploration in Inverse Constrained Reinforcement Learning—0
QueryBuilder: Human-in-the-Loop Query Development for Information Retrieval—0
Goal-Reaching Policy Learning from Non-Expert Observations via Effective Subgoal GuidanceCode0
Targeting the partition function of chemically disordered materials with a generative approach based on inverse variational autoencoders—0
Reinforcement Learning for Causal Discovery without Acyclicity Constraints—0
Emotion-Agent: Unsupervised Deep Reinforcement Learning with Distribution-Prototype Reward for Continuous Emotional EEG Analysis—0
Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction—0
Efficient Exploration in Deep Reinforcement Learning: A Novel Bayesian Actor-Critic Algorithm—0
Modeling Multi-Step Scientific Processes with Graph Transformer Networks—0
KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance—0
Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks—0
Persistent Sampling: Enhancing the Efficiency of Sequential Monte CarloCode1
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning—0
Online Learning for Autonomous Management of Intent-based 6G Networks—0
ParamsDrag: Interactive Parameter Space Exploration via Image-Space Dragging—0
Scalable Exploration via Ensemble++Code0
Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid LocomotionCode1
Preference-Guided Reinforcement Learning for Efficient ExplorationCode0
Uncertainty-Guided Optimization on Large Language Model Search TreesCode0
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