Modelling game economy with Neo4j

1. Modelling game economy ! with Neo4j

2. agenda

3. Hi, my name is Yan Cui.

4. 1MDAILY ILLION USERS ACTIVE

5. 250 MILLION DAY REQUEST PER

6. location

7. 500+ Spots

8. location episodic

9. London 2012

10. Nan Jing 2013

11. location episodic multi-player

12. herebemonstersgame.com iPad buddies

13. location episodic multi-player RPG

14. 4000 Items

15. 800 Recipes

16. 1500+ Quests

17. 100+ Monsters

18. game balancing

19. item Pricing

20. item Pricing

21. item Pricing

22. item Pricing

23. manual game balancing is SLOW

24. it is REPETITIVE

25. ERROR-PRONE! SUBJECTIVE

26. there must be a better way...

27. Hello, Neo4j The rabbit hole sounds pretty good right about now!

28. catching BIGFOOT

29. catch rate location bait attraction rate

30. as a graph in Neo4j

31. Bigfoot Alice Lake exists_in exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake

32. Bigfoot Alice Lake exists_in exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake Strength = 502! Speed = 201! Intelligence = 184 Strength = 420! Speed = 210! Technology = 240

33. Bigfoot Alice Lake exists_in exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake CatchRate = 0.774

34. Bigfoot Buy Price = 20BN! Sell Price = 482 Gold! Sellable Alice = Lake true! … exists_in exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake

35. DropRate = 0.1 Bigfoot Alice Lake exists_in exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake

36. Bigfoot Alice Lake exists_in exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake

37. Bigfoot Alice Lake exists_in can_attract Alluring Goat Bigfoot Toenail Clippings Musket-teer Trap loots can_catch Omar Lake exists_in Yowie Yeti can_catch can_catch Apprentice’s Workshop can_make Goat Honey Yeti Fur requires loots makes Alluring Goat Recipe requires requires Beeswax loots Bee Hive harvests McDonald’s Farm sells loots Goat’s Milk harvests London exists_in requires Peryton Fawn Decoy Recipe Peryton Fawn Decoy makes

41. 8000+ Nodes

42. 40000+ Edges

43. game balancing (revisited)

44. impact analysis

45. What’s the impact of upping the price of “White Bread”?

46. ITEM ITEM CRAFTS RECIPE IS_USED_IN

47. MATCH! (wb:BaseItem { Name:"White Bread"})! -[rel:CRAFTS | IS_USED_IN*1..]! ->(i:BaseItem)! RETURN i, rel, wb

48. MATCH! (wb:BaseItem { Name:"White Bread"})! -[rel:CRAFTS | IS_USED_IN*1..]! ->(i:BaseItem)! Node-[rel]->Node RETURN i, rel, wb

54. scarcity analysis

55. How scarce is “Durian” compared to “Dragonfruit”?

56. FRUIT SPOT EXISTS_IN FORAGES FRUIT TREE

57. MATCH! ! (fruit)<-[:FORAGES]-(tree)! -[:EXISTS_IN]->(spot)! WHERE! ! fruit.Name=‘Durian’ OR! fruit.Name=‘Dragonfruit’! RETURN fruit, tree, spot

58. MATCH! ! (fruit)<-[:FORAGES]-(tree)! -[:EXISTS_IN]->(spot)! Node<-[WHEREr1]-! ! Node-[r2]->Node fruit.Name=‘Durian’ OR! fruit.Name=‘Dragonfruit’! RETURN fruit, tree, spot

59. MATCH! ! (fruit)<-[:FORAGES]-(tree)! -[:EXISTS_IN]->(spot)! WHERE! ! fruit.Name=‘Durian’ OR! fruit.Name=‘Dragonfruit’! RETURN fruit, tree, spot

60. quest lines

61. ITEM ITEM AWARDS QUEST REQUIRES UNLOCKS

62. What quests come after “Year of the Horse”?

63. MATCH! (q1:Quest { Name: “Year of the Horse” })! -[:UNLOCKS]! ->(q2:Quest) ! RETURN q1, q2

64. How do you model quest progression?

65. 2. Enrich Model 1. Price Items 3. “Price” Quests

66. monster hierarchy

67. Catch me first. No, catch ME first.

68. MONSTER ITEM IS_USED_IN LOOTS RECIPE CRAFTS MONSTER ITEM CAN_ATTRACT

69. MATCH! (monster1:Monster)-[:LOOTS]->(loot)! -[r:IS_USED_IN | CRAFTS*0..]->(bait)! -[:CAN_ATTRACT]->(monster2)! RETURN monster1, monster2

70. Σ(Bait Price * Attraction Rate) Input = Output Σ(Loot Price * Drop Rate) + Gold

71. MONSTER ITEM IS_USED_IN LOOTS RECIPE CRAFTS MONSTER ITEM CAN_ATTRACT

72. NEW monster ! = More competitor for bait! = Lower attraction rate for all monsters

73. getting data into NEO4J

74. version control Game Design data

75. What changed! When did it change! Why did it change! Who changed it

76. allow multi-user editing

77. GitFlow! ! - branching strategy for Git! - used by all our developers!

78. Publisher - Validate! - Localize! - Publish

79. Publisher Flash iOS Server Neo4j

80. test data changes in isolation

81. preview changes on live

82. Localization

83. more text than first three Harry Porter books!

84. Step 1. ! ingest gettext file

85. Step 2. ! intercept string property setters

86. Step 3. ! replace string

87. Step 4. ! repeat for next language

88. intercept string property setters

89. intercept string property setters

90. replace string

91. replace string

92. target all DTOs!

93. auto-tuning trapping stats

94. Monster strength! speed! intelligence Trap strength! speed! technology

95. Monster strength! speed! intelligence Trap strength! speed! technology Catch Rate %

96. trial-and-error

97. error-prone trial-and-error laborious sub-optimal

98. genetic algorithms (in F#)

99. auto-tuning baits

100. auto-tuning baits

101. LONDON 2.0 we rewrote the entire season 1 ! quests to make them better.

102. TWICE THE FUN

103. SEASON 1 SEASON 1! (POST-REWRITE) SEASON 2

104. MORE STREAMLINED

105. QUALITY > QUANTITY

106. TWICE THE AMOUNT SUPPORT TO

107. Neo4j to the rescue!

108. Thank you!

109. theburningmonk.com @theburningmonk github.com/theburningmonk

Modelling game economy with Neo4j

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Modelling game economy with Neo4j

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