Pathfinding Peril - Speaker Deck

Slide 1

Slide 1 text

Pathﬁnding Peril Software Craftsmanship 2012 Chris Parsons and Steve Tooke Thursday, 14 June 12

Slide 2

Slide 2 text

Huh? What is it all good for... Absolutely nothing? Thursday, 14 June 12

Slide 3

Slide 3 text

Games Thursday, 14 June 12

Slide 4

Slide 4 text

Workshop Plan Introduction Graph Theory Pathﬁnding Algorithms The Maze Contest Thursday, 14 June 12

Slide 5

Slide 5 text

Graph Theory A B D C E F G Thursday, 14 June 12

Slide 6

Slide 6 text

What is it all good for... Graphs can model internet networks, data organisation, computation ﬂow, neural networks, the web, wikis, molecular structures, linguistics, social networks, biological habitats, transport networks, etc. Thursday, 14 June 12

Slide 7

Slide 7 text

Shortest route from B to C A B D C E F G Thursday, 14 June 12

Slide 8

Slide 8 text

“Brute force” A B D C E F G Thursday, 14 June 12

Slide 9

Slide 9 text

“Brute force” A B D C E F G Thursday, 14 June 12

Slide 10

Slide 10 text

“Brute force” A B D C E F G Thursday, 14 June 12

Slide 11

Slide 11 text

Weighted graphs A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 12

Slide 12 text

B - E - C will cost 19 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 13

Slide 13 text

...but B-A-G-D-C is only 9 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 14

Slide 14 text

Dijkstra's Algorithm Published 1959 Uses an ordered set of open nodes, tracking minimum cost to each Thursday, 14 June 12

Slide 15

Slide 15 text

Shortest route from B to C A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 16

Slide 16 text

Visit B Node Cost B 0 A (from B) 3 F (from B) 3 E (from B) 17 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 17

Slide 17 text

Visit A Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from B) 17 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 18

Slide 18 text

Visit F Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from B) 17 (25 is bigger) A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 19

Slide 19 text

Visit G Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 D (from G) 8 E (from B) 17 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 20

Slide 20 text

Visit D Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 D (from G) 8 C (from D) 9 E (from B) 17 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 21

Slide 21 text

Visit C - we’re done! Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 D (from G) 8 C (from D) 9 E (from B) 17 A B D E F G 3 3 17 2 2 3 22 1 C Thursday, 14 June 12

Slide 22

Slide 22 text

Updated weights A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 23

Slide 23 text

Visit B Node Cost B 0 A (from B) 3 F (from B) 3 E (from B) 17 A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 24

Slide 24 text

Visit A Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from B) 17 A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 25

Slide 25 text

Visit F Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from F) 6 A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 26

Slide 26 text

Visit G Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from F) 6 D (from G) 8 A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 27

Slide 27 text

Visit E Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from F) 6 C (from E) 8 D (from G) 8 A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 28

Slide 28 text

Visit C - we’re done! Node Cost B 0 A (from B) 3 F (from B) 3 G (from A) 6 E (from F) 6 C (from E) 8 D (from G) 8 A B D E F G 3 3 17 2 2 3 3 1 C Thursday, 14 June 12

Slide 29

Slide 29 text

A* algorithm Published 1968 Variation on Dijkstra, using a heuristic to cut down on nodes to visit Thursday, 14 June 12

Slide 30

Slide 30 text

Distance Heuristic A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 31

Slide 31 text

Visit B Node Cost Order B 0 10 (0+10) F 3 21 (3+18) A 3 26 (3+23) E 17 40 (17+13) A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 32

Slide 32 text

Visit F Node Cost Order B 0 10 (0+10) F 3 21 (3+18) A 3 26 (3+23) E 17 30 (17+13) A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 33

Slide 33 text

Visit A Node Cost Order B 0 10 (0+10) F 3 21 (3+18) A 3 26 (3+23) G 6 26 (6+20) E 17 30 (17+13) A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 34

Slide 34 text

Visit G Node Cost Order B 0 10 (0+10) F 3 21 (3+18) A 3 26 (3+23) G 6 26 (6+20) D 8 20 (8+12) E 17 30 (17+13) A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 35

Slide 35 text

Visit D Node Cost Order B 0 10 (0+10) F 3 21 (3+18) A 3 26 (3+23) G 6 26 (6+20) D 8 20 (8+12) C 9 9 (9 +0) E 17 30 (17+13) A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 36

Slide 36 text

Visit C - we’re done! Node Cost Order B 0 10 (0+10) F 3 21 (3+18) A 3 26 (3+23) G 6 26 (6+20) D 8 20 (8+12) C 9 9 (9 +0) E 17 30 (17+13) A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 37

Slide 37 text

Non-admissible Heuristic A 23 B 10 D 12 E 13 F 18 G 20 3 3 17 2 2 3 22 1 C 0 Thursday, 14 June 12

Slide 38

Slide 38 text

Different Heuristics Dijkstra no heuristic A* exact distance (admissible) http://en.wikipedia.org/wiki/A*_search_algorithm http://en.wikipedia.org/wiki/Dijkstra%27s_algorithm A* over-egging distance (non-admissible) Thursday, 14 June 12

Slide 39

Slide 39 text

Summary Thursday, 14 June 12

Slide 40

Slide 40 text

Summary Brute force approach: O(n²) (ouch!) Thursday, 14 June 12

Slide 41

Slide 41 text

Summary Brute force approach: O(n²) (ouch!) Dijkstra: guarantees best path but still can be slow Thursday, 14 June 12

Slide 42

Slide 42 text

Summary Brute force approach: O(n²) (ouch!) Dijkstra: guarantees best path but still can be slow A*: depending on Heuristic can trade speed for best path Thursday, 14 June 12

Slide 43

Slide 43 text

Summary Brute force approach: O(n²) (ouch!) Dijkstra: guarantees best path but still can be slow A*: depending on Heuristic can trade speed for best path Admissible Heuristics (never overestimating cost) is the sweet spot for A* Thursday, 14 June 12

Slide 44

Slide 44 text

Your turn Visit http://172.31.31.25:3000 for the tournament We’ll run an overﬂow server if we need to The rules for the game are shown Rest of this session for practice (1m rounds) Proper contest will be 5m rounds after the break Thursday, 14 June 12

Slide 45

Slide 45 text

BDD Kickstart Matt Wynne + myself running our BBC courses publicly Central London, 16th - 19th July £450/day, use code SC2012 for 20% off http://bddkickstart.com Thursday, 14 June 12

Slide 46

Slide 46 text

Thanks! Chris Parsons @chrismdp - http://pa.rsons.org Steve Tooke @tooky - http://heavi.es Thursday, 14 June 12