In Experiment 1, we tested two hypotheses for how people perform assignment inference.
We proposed and evaluated two hypotheses about how people perform assignment color inference.
We propose that to interpret color-coding systems, people perform assignment inference to determine how colors map onto concepts.
The genetic algorithm has been executed to perform assignment of the runnables to cores with timing characteristics for the initial PowerUp mode.
Experiment 2 tested whether people can still perform assignment inference with a larger set of six objects and six colors that contain conflicts due to one-to-many and many-to-one mappings.
Thirdly, we performed assignment tests using STRUCTURE 2.2 [29], [30], [30] to determine to what extent the patterns obtained with aggression tests correlated with genetic differentiation between supercolonies.
Finally, we used structure to perform assignment tests to identify potential migrants within the dataset.
We performed assignment tests for each individual using smoothed and continuous assignment methods [ 11], implemented in the SCAT software program http://stephenslab.uchicago.edu/software.html.html
We then utilized the program STRUCTURE 2.2 on the multilocus AFLP data to assess hybrid origin and perform assignment tests for the putative hybrids [ 66, 67].
We performed assignment runs for the samples using the Rannala and Mountain [ 89] Bayesian individual assignment method as implemented in the program GENECLASS2 [ 90] to estimate the likelihood that a wolf originated from a given temporal population.
Comments in braces indicate where the algorithm performs assignment to pruner-lists, as per conditions (2) and (3), and pruning, according to the different cases of Theorems 2 and 3.
