diff --git a/CONTRIBUTORS b/CONTRIBUTORS
index 28da378..0f49c40 100644
--- a/CONTRIBUTORS
+++ b/CONTRIBUTORS
@@ -1,4 +1,7 @@
 0.9
+    Robert Patton for being a documentation guinea pig. Documentation added for probes and min()/max() for minimization problems.
+
+0.8.1
     Lucas McCombs for improvements to crossover operators, parent/offspring tracking, plotting, and more.
 
 0.8
diff --git a/docs/source/common_problems.rst b/docs/source/common_problems.rst
index 1bbc181..084d7ce 100644
--- a/docs/source/common_problems.rst
+++ b/docs/source/common_problems.rst
@@ -3,6 +3,30 @@ Common Problems
 
 Here we address common problems that may arise when using LEAP.
 
+`min()` returns the worst individual for minimization problems
+--------------------------------------------------------------
+
+`min()` and `max()` works the opposite you may expect for minimization problems
+because the `<` operator has been overriden to consider fitness scalars that are
+numerically less than than another to be "better".  So `min()` takes into consideration
+the problem semantics not the raw number values.
+
+E.g., for a given minimization problem:
+
+.. code-block:: python
+
+    min(parents).fitness
+    Out[2]: 66.49057507514954
+    max(parents).fitness
+    Out[3]: 59.87865996360779
+
+The above shows that the value `59.87865996360779` is "better" than
+`66.49057507514954` even though _numerically_ it is less than the other value.
+
+It was important for LEAP to override the `<` operator for `Individual`s because
+it uses native sort operations to find the "best" and "worst", and so minimization vs.
+maximization semantics needed to be taken into account.
+
 Missing pipeline operator arguments
 -----------------------------------