arXiv Machine Learning September 3, 2026 By Antonio Mone, Zuzanna Osika, Florian Felten, Pradeep K. Murukannaiah, Mark Fuge, Frans A. Oliehoek, Luciano Cavalcante Siebert

Objective-Behavior Alignment: Diagnostics for MORL Policy Selection

Read the original on arXiv Machine Learning →

The paper introduces a diagnostic workflow for multi‑objective reinforcement learning (MORL) that reveals behavioral differences among policies on the Pareto front, which are not apparent from value vectors alone. It offers quantitative and visual tools to inspect these variations and demonstrates their effectiveness on both simple grid tasks and more complex continuous‑control benchmarks.

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