Author

Martin Tappler

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Book Open access Aug 2026

ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning

This work presents ATLAS (Automata Learning for Agent Trajectory Analysis and Strategy Discovery), an approach for recovering interpretable behavioral models from agent trajectories that enable systematic understanding and analysis of otherwise opaque AI agents.

Ignacio D. Lopez-Miguel, A. Happe, J. Cito et al. · Proceedings of the ACM/IEEE... · 1 citation

Preprint Jul 2026

ORCAID: Oblique Rule-Based Continuous-Action Interpretation for Deep RL Policies

This work introduces ORCAID, a novel method for extracting interpretable rule-based policies from RL agents operating in mixed continuous-discrete environments with continuous action spaces, with an efficient oblique decision tree training algorithm that partitions the state space by hyperplanes and fits local linear m...

Ignacio D. Lopez-Miguel, E. Bartocci, Thomas Eiter et al. · 0 citations