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Mechanical Puzzle Design
as a
Man-Machine Collaboration
Pavel Curtis
Pavel’s Puzzles
http://www.pavelspuzzles.com
Overview
• Explore development of my puzzle design process
• How I did (or would) design three specific puzzles
• Lessons I’ve learned along the way
On the Problem of Spoilers
• How to describe my process without spoiling puzzles?
• Approach #1: Some designs are hard to spoil!
• #2: Spoil somebody else’s puzzles! 
• #3: Spoil a puzzle that’s currently unavailable!
• And hope you’ll have forgotten by the time it is available…
Birth of a Puzzle Design
• Summer 2000: International Puzzle Party
• To be held in Tokyo, Japan
• The Japanese flag is very simple, elegant: dissect it?
• Break it up into 12 ‘domino’ shapes
• A 4×6 tray yields 12 pieces: that’s a good number
• Feels way too easy…
• Make the pieces double-sided?
• It should have a unique solution, right?
Hinomaru:
The Japanese Flag Puzzle
Good Idea! Now What?
• Is it possible to design pieces with a unique solution?
• Time for software!
• Compute all possible ways to dissect a 4×6 rectangle
into twelve 1×2 domino shapes
• Answer: something like 261 distinct dissections

• Manually select the one that looks most ‘random’
• Assign faces to the backs such that solution is unique
• Lots and lots of assignments work: how to choose?
• Try to use each face design the same number of times?
Design Complete!
On to Test Solving…
• I abuse my friends.
• A lot.

• The prototype:

• First tester (a genius): 2 hours and 30 minutes!
• Second tester (super-genius): 45 minutes!
• Making it hard enough was not the problem…
• Can it be solved without exhaustive, brute-force search?
Lessons Learned I:
Pavel’s Three Laws
• It’s easy to design a hard puzzle.
• It’s hard to design a good puzzle.
• It’s good to design an easy puzzle.
(At least sometimes)
Lessons Learned II:
One Useful Design Process
• Imagine an interesting puzzle ‘story’
• Use software to search for puzzles that tell that story
• Almost always, only two possible outcomes
• No such puzzles? ‘Open up’ the story
• Too many puzzles? Add more detail to the story
Example #2:
‘Four Sleazy Pieces’
• Designed by Stewart Coffin
• American ‘elder statesman’ of puzzle design

• Let’s pretend that I designed this puzzle
• A non-spoiling analogue for my ‘Sleazier’ puzzle
• It was inspired by my (failing at) solving Stewart’s puzzle!
First, the Story
• Pack a square tray with polyominoes
• Polyominoes = shapes made of multiple squares
Make the Tray a Weird Size
• Not an integral side-length:
~5.8
units

• Experienced puzzlers know
what this means
• Anything weird is that way
for a reason
Then Double-Cross Them!
• Pieces do go in at an angle, but not that one!

• (It is called ‘Four Sleazy Pieces’…)
Time for Software!
• Find all ways to dissect the goal shape
• Reusable module #1: shape partitioning algorithm

• For each possible dissection, perform solving tests
• Reusable module #2: shape solving algorithm

• Must solve goal shape in exactly one way
• Must solve these shapes in no ways:
Drowning in an Ocean of Puzzles!
• Thousands or even millions of dissections work!
• Add more constraints to the story:
• No straight pieces
• No duplicate pieces
• All pieces about the same size

• Still too many? Talk to my wife!
• a.k.a, my ‘sadism consultant’

• “Can you make it almost solve 5×5?”
• Pieces must solve these shapes:
Puzzles that are Stories
• A ‘story puzzle’ is solved in ‘chapters’
• Goal of first chapter is (fairly) obvious
• Solving that chapter leads to a new puzzle
• Welcome to Chapter Two!

• Final chapter yields a satisfying conclusion
• Typically an appropriate word or phrase

• Story puzzles usually have 3 to 5 chapters
Example #3:
Holiday Discount Puzzle 2012
• Genesis: Can this shape make a puzzle?
• Eight square pieces,
each with or without certain corners
• Need solution to be unique
• Ensures a consistent ‘next chapter’

• Answer: create some kind of picture
• Pieces must have ambiguous placements
Chapter One
• Eight pieces:

• Goal: make a solid diamond:
• Each piece could fit at
two corners and two edges
Chapter Two
• Somehow read a message off the assembly
• Thus, need letters on the pieces:
A

R

P

L

I

E

S

S

E

S

E

R

T

H

R

A

N

O

E

T

R

E

E

D

W

T

A

C

E

• Solver must infer: read clockwise around the
diamond, ignoring other letters
Chapter Three
• Message suggests reading the other letters
• But doesn’t explain exactly how

• Solver must infer: read left to right, top to bottom
• Result: “ANSWER IS _______”

• Only three chapters here
• Want the discount puzzle to be on the easy side
When Software Can’t Help
• Many puzzle searches can’t be automated:
• Disentanglement / topological puzzles
• Trick-opening boxes
• My “Get a Clue!” puzzle

• This category is growing for me
• Still lots of design lessons to learn!
Story-First Design
• Craft a pleasing solving story
• Use whatever tools work to search for
puzzles that tell that story

• Revise or refine the story as indicated
• Treat test-solvers as story critics
What Story Would You
Like to Solve Today?

Thank you.

Pavel’s Puzzles
http://www.pavelspuzzles.com
High-quality mechanical puzzles, direct from the designer!

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Mechanical puzzle design

  • 1. Mechanical Puzzle Design as a Man-Machine Collaboration Pavel Curtis Pavel’s Puzzles http://www.pavelspuzzles.com
  • 2. Overview • Explore development of my puzzle design process • How I did (or would) design three specific puzzles • Lessons I’ve learned along the way
  • 3. On the Problem of Spoilers • How to describe my process without spoiling puzzles? • Approach #1: Some designs are hard to spoil! • #2: Spoil somebody else’s puzzles!  • #3: Spoil a puzzle that’s currently unavailable! • And hope you’ll have forgotten by the time it is available…
  • 4. Birth of a Puzzle Design • Summer 2000: International Puzzle Party • To be held in Tokyo, Japan • The Japanese flag is very simple, elegant: dissect it? • Break it up into 12 ‘domino’ shapes • A 4×6 tray yields 12 pieces: that’s a good number • Feels way too easy… • Make the pieces double-sided? • It should have a unique solution, right?
  • 6. Good Idea! Now What? • Is it possible to design pieces with a unique solution? • Time for software! • Compute all possible ways to dissect a 4×6 rectangle into twelve 1×2 domino shapes • Answer: something like 261 distinct dissections • Manually select the one that looks most ‘random’ • Assign faces to the backs such that solution is unique • Lots and lots of assignments work: how to choose? • Try to use each face design the same number of times?
  • 7. Design Complete! On to Test Solving… • I abuse my friends. • A lot. • The prototype: • First tester (a genius): 2 hours and 30 minutes! • Second tester (super-genius): 45 minutes! • Making it hard enough was not the problem… • Can it be solved without exhaustive, brute-force search?
  • 8. Lessons Learned I: Pavel’s Three Laws • It’s easy to design a hard puzzle. • It’s hard to design a good puzzle. • It’s good to design an easy puzzle. (At least sometimes)
  • 9. Lessons Learned II: One Useful Design Process • Imagine an interesting puzzle ‘story’ • Use software to search for puzzles that tell that story • Almost always, only two possible outcomes • No such puzzles? ‘Open up’ the story • Too many puzzles? Add more detail to the story
  • 10. Example #2: ‘Four Sleazy Pieces’ • Designed by Stewart Coffin • American ‘elder statesman’ of puzzle design • Let’s pretend that I designed this puzzle • A non-spoiling analogue for my ‘Sleazier’ puzzle • It was inspired by my (failing at) solving Stewart’s puzzle!
  • 11. First, the Story • Pack a square tray with polyominoes • Polyominoes = shapes made of multiple squares
  • 12. Make the Tray a Weird Size • Not an integral side-length: ~5.8 units • Experienced puzzlers know what this means • Anything weird is that way for a reason
  • 13. Then Double-Cross Them! • Pieces do go in at an angle, but not that one! • (It is called ‘Four Sleazy Pieces’…)
  • 14. Time for Software! • Find all ways to dissect the goal shape • Reusable module #1: shape partitioning algorithm • For each possible dissection, perform solving tests • Reusable module #2: shape solving algorithm • Must solve goal shape in exactly one way • Must solve these shapes in no ways:
  • 15. Drowning in an Ocean of Puzzles! • Thousands or even millions of dissections work! • Add more constraints to the story: • No straight pieces • No duplicate pieces • All pieces about the same size • Still too many? Talk to my wife! • a.k.a, my ‘sadism consultant’ • “Can you make it almost solve 5×5?” • Pieces must solve these shapes:
  • 16. Puzzles that are Stories • A ‘story puzzle’ is solved in ‘chapters’ • Goal of first chapter is (fairly) obvious • Solving that chapter leads to a new puzzle • Welcome to Chapter Two! • Final chapter yields a satisfying conclusion • Typically an appropriate word or phrase • Story puzzles usually have 3 to 5 chapters
  • 17. Example #3: Holiday Discount Puzzle 2012 • Genesis: Can this shape make a puzzle? • Eight square pieces, each with or without certain corners • Need solution to be unique • Ensures a consistent ‘next chapter’ • Answer: create some kind of picture • Pieces must have ambiguous placements
  • 18. Chapter One • Eight pieces: • Goal: make a solid diamond: • Each piece could fit at two corners and two edges
  • 19. Chapter Two • Somehow read a message off the assembly • Thus, need letters on the pieces: A R P L I E S S E S E R T H R A N O E T R E E D W T A C E • Solver must infer: read clockwise around the diamond, ignoring other letters
  • 20. Chapter Three • Message suggests reading the other letters • But doesn’t explain exactly how • Solver must infer: read left to right, top to bottom • Result: “ANSWER IS _______” • Only three chapters here • Want the discount puzzle to be on the easy side
  • 21. When Software Can’t Help • Many puzzle searches can’t be automated: • Disentanglement / topological puzzles • Trick-opening boxes • My “Get a Clue!” puzzle • This category is growing for me • Still lots of design lessons to learn!
  • 22. Story-First Design • Craft a pleasing solving story • Use whatever tools work to search for puzzles that tell that story • Revise or refine the story as indicated • Treat test-solvers as story critics
  • 23. What Story Would You Like to Solve Today? Thank you. Pavel’s Puzzles http://www.pavelspuzzles.com High-quality mechanical puzzles, direct from the designer!