Update README.md

README.md

@@ -38,12 +38,29 @@ of machine learning models to learn and apply logical reasoning within a visual
 
 ### Supported Tasks and Leaderboards
 
+Logical complexity:
+
 (i)   Theory X: The train has either a short, closed car or a car with a barrel load is somewhere behind a car with a golden vase load. This rule was originally introduced as "Theory X" in the new East-West Challenge.
 
 (ii)  Numerical rule: The train has a car where its car position equals its number of payloads which equals its number of wheel axles.
 
 (iii) Complex rule: Either, there is a car with a car number which is smaller than its number of wheel axles count and smaller than the number of loads, or there is a short and a long car with the same colour where the position number of the short car is smaller than the number of wheel axles of the long car, or the train has three differently coloured cars. We refer to Tab. 3 in the supp. for more insights on required reasoning properties for each rule.
 
+Visual complexity:
+
+(i) Realistic train representaions.
+(ii) Block representation.
+
+Train lengths:
+
+(i) A train carrying 2-4 cars.
+(ii) A train carrying 7 cars.
+
+Train attribute distributions:
+
+(i) Michalski attribute distribution.
+(ii) Random attribute distribution.
+
 ### Languages
 
 English