# Duplicate AICc values for multiple models with interactions

I am going through a model selection process with a mixed-model with 3 variables: A, B, and C. B and C are orthogonal factors. B or C may interact with A, so my full model would be:

fixed:

Y ~ A + B + C + A*B + A*C


random:

~1|D


When I run my analysis, I get four models sharing the lowest AICc.

Y ~ B + A*C
Y ~ A + B + A*C
Y ~ B + C + A*C
Y ~ A + B + C + A*C


I am very confused about what is going on. Obviously there is an interaction between A and C, but how can they all have the same AICc value? Where do I go from here in model selection?