The article proposes a new method for weighting characters according to their homoplasy during tree search, which is non-iterative and does not require independent estimations of weights. The method is based on searching trees with maximum total fit, where character fits are defined as a concave function of homoplasy. This approach ensures that differences in steps for characters with more homoplasy are less influential when comparing trees. The reliability of characters is estimated during the analysis, and the "fittest" trees imply that characters are maximally reliable, resolving character conflict in favor of characters with less homoplasy. The method contrasts with successive weighting, which is iterative and依赖于初始权重估计。The new method produces trees that, given the constraints imposed by character interaction, imply the characters to be maximally reliable. The article also discusses the limitations of traditional methods and the importance of considering homoplasy in character weighting.The article proposes a new method for weighting characters according to their homoplasy during tree search, which is non-iterative and does not require independent estimations of weights. The method is based on searching trees with maximum total fit, where character fits are defined as a concave function of homoplasy. This approach ensures that differences in steps for characters with more homoplasy are less influential when comparing trees. The reliability of characters is estimated during the analysis, and the "fittest" trees imply that characters are maximally reliable, resolving character conflict in favor of characters with less homoplasy. The method contrasts with successive weighting, which is iterative and依赖于初始权重估计。The new method produces trees that, given the constraints imposed by character interaction, imply the characters to be maximally reliable. The article also discusses the limitations of traditional methods and the importance of considering homoplasy in character weighting.