R2L: Reliable Reinforcement Learning: Guaranteed Return & Reliable Policies in Reinforcement Learning

PAVe: Agentenbasierte Fahrzeugnavigation mit semantischem Kontext

How to Build a Model-Native Agent That Learns Internal Planning, Memory, and Multi-Tool Reasoning Through End-to-End Reinforcement Learning

Reinforcement Learning for Long-Horizon Unordered Tasks: From Boolean to Coupled Reward Machines

Advancing site-specific disease and pest management in precision agriculture: From reasoning-driven foundation models to adaptive, feedback-based learning

How Exploration Agents like Q-Learning, UCB, and MCTS Collaboratively Learn Intelligent Problem-Solving Strategies in Dynamic Grid Environments

Confounding Robust Deep Reinforcement Learning: A Causal Approach