exploration

EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration ICML 2025 Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models ICLR 2025 Logarithmic regret of exploration in average reward Markov decision processes COLT 2025 PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization ICLR 2025 Position: Constants are Critical in Regret Bounds for Reinforcement Learning ICML 2025 Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration ICML 2025 The Role of Environment Access in Agnostic Reinforcement Learning (Extended Abstract) COLT 2025 Towards Improving Exploration through Sibling Augmented GFlowNets ICLR 2025 Unsupervised Skill Discovery as Exploration for Learning Agile Locomotion CoRL 2025 Exploration and Anti-Exploration with Distributional Random Network Distillation ICML 2024 Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States ICML 2024 Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations ICML 2024 Risk-Sensitive Reward-Free Reinforcement Learning with CVaR ICML 2024 When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions ICML 2024 Efficient Exploration and Value Function Generalization in Deterministic Systems NeurIPS 2013 (More) Efficient Reinforcement Learning via Posterior Sampling NeurIPS 2013 Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress NeurIPS 2012 Hierarchical Optimistic Region Selection driven by Curiosity NeurIPS 2012 Multi-resolution Exploration in Continuous Spaces NeurIPS 2008