Eugenics thinks that some genes are clearly better than others but, for example, in game theory there are competitive solutions where the best solution is a probability distribution of different tactics/genes so there are no clearly better genes (hawk-dove example). In society, for example, doctors and judges are both needed so there are no clearly better professions/individuals. One can then say that successful businessmen or athletes who get millions should not get more money than successful doctors, scientists and judges because they all are needed.
Additionally, if an environment changes and population must adapt as fast as possible information theory shows that the fastest way to adapt (in information theoretic sense [has few problems]) to new situation is to calculate using bayesian inference. This means calculations/optimization using population distributions again and the tails of the less probable genes must be supported somehow.
Also, greedy optimization, which often reduces to simple competition based optimization (gradient ascend), gets stuck to local maximas (See the picture). This means the good optimization of genes may require more than relatively simple changes, the competition and the survival of the fittest. To escape from a local maxima, a search through potentially worse solutions is required. So this means that the weaker ones should be supported by the stronger ones. (Note that if we add money to the equation individuals can collect money at local maximum and then do expensive search of new better optimum using money they have. But currently we cannot change our genes using money so genes cannot be changed to search better optimums after resources are collected at the local maxima. (To partly work around this limitation parents support their children to grow to adults so the collected resources at local maxima are used to try new solutions.))
Tomas Ukkonen, M.Sc.