Arnaud Lequen

PQLRM achieves faster convergence and superior policy synthesis in multi-objective reinforcement learning, outperforming traditional methods in complex reward scenarios.

Learning admissible heuristics through LLM-driven program synthesis can yield faster evaluations and deeper domain insights without sacrificing optimality.