Puzzles have long served as a benchmark for evaluating the reasoning capabilities of AI systems in sequential decision making. Yet, as a new arXiv paper notes, approaches originating from different paradigms are seldom compared under a unified set of criteria, making it difficult to assess relative progress.
The paper, posted as arXiv:2610.11696, proposes a 3D characterization framework designed to bring coherence to such evaluations. While the abstract does not detail the three dimensions, the framework is positioned as a way to systematically compare intelligent sequential decision-making across diverse AI approaches.
Because the source is a single preprint abstract, the specifics of the framework remain limited. The paper's contribution, as stated, is the framework itself and the motivation for unified comparison—an important step toward more meaningful benchmarking in this area.