Assaf Hallak

Our paper From Actions to Words: Towards Abstractive-Textual Policy Summarization in RL was accepted to AAMAS 2026: arxiv.org/abs/2503.10509 (led by @saharad1) We study how to explain reinforcement learning policies at a global level by summarizing agent behavior patterns