Puzzles: Solving and Writing Tips

1 / 47

Puzzles: Solving and Writing Tips

Puzzles: Solving and Writing Tips

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

1. Puzzles:Solving and Writing Tips ΣUMS talk - 5/4/12 Sean Gardiner

2. Introduction • Puzzles are presented as a bunch of words and/or pictures, and little else • The goal is always to extract a word or phrase • Done by searching for patterns and identifying and utilising themes(cf. solving maths problems) • The crux is the intuitive leap(s) • Always motivatable, but rarely obvious • Different categories (based on appearance)

3. Word Puzzles • Words can have multiple properties: • Meaning (double meaning, “cryptic” definitions) • Letter/constituent properties (too many to list!) • Sound (rhymes, phonetics, ...) • Varied forms of presentation: • List • Hidden (e.g. in a paragraph/poem) • Codes (Caesar cypher, Morse, Braille, alphanumeric...) • Clues (straight, cryptic)

4. Solving Word Puzzles • Huge range of word puzzle mechanics • Expect puzzles to use at least two properties • Always look for patterns(in letters/meanings) • Numbers => convert or index(usually)

5. Recapitulation – Corey Plover (MUMS 2010)

6. Recapitulation – Corey Plover (MUMS 2010)

7. Wockyjabber – Sean Gardiner (ΣUMS 2010)

8. Headless Snake – Steven Irrgang (CiSRA 2009)

9. Kangaroo Jack – Corey Plover (MUMS 2011)

10. Picture Puzzles • Pure picture puzzles rely only on image interpretation • Usually employ different perspectives as a mechanic • Sometimes drawing/adding to the picture is required

11. Solving Picture Puzzles • Be artistic! – Think visually (or know someone who can) • While puzzle type can vary wildly, the answer extraction (last step) is very restricted: • Find/construct letters that spell out the answer • Find/construct an easily and uniquely-identifiable image or set of images (more likely)

12. Smilies – Andrew Shellshear (CiSRA 2008)

13. Smilies – Andrew Shellshear (CiSRA 2008)

14. Concyclicity– Ivan Guo (ΣUMS 2009)

15. Concyclicity– Ivan Guo (ΣUMS 2009)

16. Meet Your Match– Andrew Coker (CiSRA 2009)

17. Logic Puzzles • “Logic” puzzles are self-contained and often original ideas: • Follow a series of steps(usually disguised) • Identify/determine a rule set • Reinterpretations(e.g. board games) • All puzzle types overlap with this one in one way or another

18. Solving Logic Puzzles • An inherent property of logic puzzles is that everything needed to solve one is already on the page in some capacity (and usually there’s only just enough information) • In some cases new rules/steps might be implied from old ones (mechanic repetition is common) • Using deduction can often prove just as useful as induction

19. Art – Andrew Shellshear (CiSRA 2010)

20. The Drover – Sam Chow & Stephen Muirhead (MUMS 2011)

21. Characterisation – Sean Gardiner (ΣUMS 2010)

22. Latin Pipes – David McLeish (CiSRA 2010)

23. Latin Pipes – David McLeish (CiSRA 2010)

24. Construction Puzzles • Basically a mix of picture and logic types • Involve cutting/folding/pasting • The construction rules are usually made clear • Most basic construction ideas have already been exhausted

25. Solving Construction Puzzles • First step: Always cut everything out! • Expect the construction step to be relevant to the overall puzzle: • If cutting is involved, there ought be a reason the pieces were originally separated • If folding is involved, you’ll want to use the 3D property at some point

26. Continuity – David Morgan-Mar (CiSRA 2007)

27. Duplex – Ivan Guo (ΣUMS 2010)

28. Research Puzzles • These tend to contain very specific descriptions/jargon/pictures/themes: • Rarely solvable without doing some research • Can involve retrieving facts/stats, recognising pictures/music, etc.

29. Solving Research Puzzles • Research! • Wikipedia/Google/specialist websites • Ask around – the topic might be someone’s field of expertise • Try to identify the puzzle’s theme as early as possible, as this will greatly help narrow down the research

30. Super Effective – Scott Mooney (ΣUMS 2010)

31. Kingfisher – Sam Chow (MUMS 2008)

32. Identikit – Andrew Shellshear (CiSRA 2010)

33. Identikit – Andrew Shellshear (CiSRA 2010)

34. General Solving Tips • Practise! – Lots of puzzles in archives • Work with friends – Multiple perspectives • Pay close attention to hints – Sometimes there’s more to a hint than its surface meaning • Don’t be afraid to guess • Keep a checklist of what elements of the puzzle you have/haven’t used yet (not foolproof) • Try to think from the writer’s perspective

35. The ΣUMS Commandments • Minimal extraneous information • Minimal ambiguities(in clues, answers, etc.) • No specialist knowledge required • No repeated mechanics (i.e. from other puzzles) • All steps should be motivatable • Hints should ideally be written such that they help solvers stuck at any step • Meta should require majority of puzzles solved

36. More ΣUMS Commandments • Puzzles solvable without using title/story • Everything needed is contained in the PDF (static) • Minimise number of research/casebash puzzles • Meta: disallow backsolving and involve story • Rangeof puzzle types and difficulties • Thematic mechanics/presentation/title/answer • Enjoyableintuitive leap – if solving the puzzle wasn’t fun, we’ve failed

37. Bad Example: Disc – Julian Assange (MUMS 2004)

38. Bad Example: Disc – Julian Assange (MUMS 2004)

39. Writing Puzzles • Start with an idea/theme and build the puzzle naturally around it • Test every iteration with new people • Write good hints (difficult!) • Be aware of the other puzzles • Is your mechanic or theme too similar to another? • Does the Meta enforce any requirements?

40. Example: Porcus – Sean Gardiner (ΣUMS 2010) • Idea: Pig Latin pairs (e.g. wrecks  X-ray) • Theme: Pigs! • Expand: Pigpen cypher – • Restrictions: • Not many Pig Latin pairs • Can only use letters A-R to avoid cheating • Want the answer to be pig-related

41. Example: Porcus – Sean Gardiner (ΣUMS 2010)

42. Example: Porcus – Sean Gardiner (ΣUMS 2010) • Refinement: • Adjusted some of the clues to be fairer • Removed the alphabetic ordering restriction to include a better hint • Changed black/white to pink/green (to avoid people trying to mix colours – minimise confusion) • Changed rocks to “biscuits” (more thematic)

43. Example: Porcus – Sean Gardiner (ΣUMS 2010)

44. References • CiSRA Puzzle Competition: • http://puzzle.cisra.com.au/ • MUMS Puzzle Hunt: • http://www.ms.unimelb.edu.au/~mums/puzzlehunt/ • ΣUMS Puzzle Hunt: • http://www.maths.usyd.edu.au/u/sums/puzzlehunt