Difficulty Rating of Sudoku Puzzles: An Overview and Evaluation
  How can we predict the difficulty of a Sudoku puzzle? We give an overview of
difficulty rating metrics and evaluate them on extensive dataset on human
problem solving (more then 1700 Sudoku puzzles, hundreds of solvers). The best
results are obtained using a computational model of human solving activity.
Using the model we show that there are two sources of the problem difficulty:
complexity of individual steps (logic operations) and structure of dependency
among steps. We also describe metrics based on analysis of solutions under
relaxed constraints -- a novel approach inspired by phase transition phenomenon
in the graph coloring problem. In our discussion we focus not just on the
performance of individual metrics on the Sudoku puzzle, but also on their
generalizability and applicability to other problems.
