← Learning Types
Machine Learning › Learning Types ›

Exploration

86 directly classified papers

Papers per year

Papers

Entropy-based Exploration Conduction for Multi-step Reasoning ACL 2025
Learning Joint Behaviors with Large Variations AAAI 2025
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learning AAAI 2025
Nearly Tight Bounds for Exploration in Streaming Multi-Armed Bandits with Known Optimality Gap AAAI 2025
Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning NIPS 2024
Leveraging Separated World Model for Exploration in Visually Distracted Environments NIPS 2024
Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration AAAI 2024
Beyond Optimism: Exploration With Partially Observable Rewards NIPS 2024
Controlled maximal variability along with reliable performance in recurrent neural networks NIPS 2024
How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach NIPS 2024
Preference-based Pure Exploration NIPS 2024
The Value of Reward Lookahead in Reinforcement Learning NIPS 2024
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus NIPS 2024
Optimal Top-Two Method for Best Arm Identification and Fluid Analysis NIPS 2024
Population-Based Diverse Exploration for Sparse-Reward Multi-Agent Tasks IJCAI 2024
Settling Decentralized Multi-Agent Coordinated Exploration by Novelty Sharing AAAI 2024
Adaptive Exploration for Data-Efficient General Value Function Evaluations NIPS 2024
QUIS: Question-guided Insights Generation for Automated Exploratory Data Analysis EMNLP 2024
Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning ICML 2023
Networked Restless Bandits with Positive Externalities AAAI 2023
Reinforced Approximate Exploratory Data Analysis AAAI 2023
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations NIPS 2023
Optimistic Active Exploration of Dynamical Systems NIPS 2023
MIMEx: Intrinsic Rewards from Masked Input Modeling NIPS 2023
Efficient Exploration in Continuous-time Model-based Reinforcement Learning NIPS 2023