MAS-Algorithm is a multi-agent workflow that improves AI acceptance rates on algorithmic problems by 6.48% on average, outperforming parameter-efficient fine-tuning.
− For maximum Manhattan distance, we can calculate: − max((x1+y1) − (x2+y2)) and max((x1−y1) − (x2−y2)) − This is done by tracking max and min of (x+y) and (x−y) for both players
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MAS-Algorithm: A Workflow for Solving Algorithmic Programming Problems with a Multi-Agent System
MAS-Algorithm is a multi-agent workflow that improves AI acceptance rates on algorithmic problems by 6.48% on average, outperforming parameter-efficient fine-tuning.