AI in board games can be applied to many classic and popular games using different techniques. Board games abstract real-world scenarios onto boards and have evolved from ancient wars to modern video games. Early board games included Senet from 3500BC and Go from 2200BC while modern card games like Mahjong and Poker became popular in the 19th century. American and German styles of board games differ in themes, conflict levels, and luck factors. Mechanics like bidding, betting, bluffing, and partnerships can be modeled using techniques from auction theory, gambling, and information theory. Popular games employ draw/discard, hand management, set collection, trick-taking, and player elimination which influence AI approaches.

1. AI in board games
meteor
2017-4-7

2. What’s a board game?
Literally, A board game has two parts: a board, and a
game.
Sure there’re different boards!
Chess board Round Table Duel
Where’s the
board…?

3. Why board games?
Board games come from the abstraction of real
world.
Chess/Go <- Ancient Wars
Board games are foundation of modern video
games.
Chainmail -> DND -> Western RPG

4. History of board games(I)
3500BC - 3000BC: Senet and Backgammon - Oldest
known board games
2200BC: Go - Ancient Chinese board game
800AD: Leaf Game - Earliest card games in China
19th Century: Mahjong and Poker - Popular modern card
games
1933: Monopoly - Fruits of the Great Depression

5. History of board games(II)
1959: Risk - Modern War Game(Aka American-style
board games)
1964: Acquire - First Eurogames(Aka German-style
board games)
1971: Chainmail - Ancestor of DND and West RPG
1995: The Settlers of Catan - One of the greatest
Eurogames
21st Century: Where to go?

6. Study of Backgammon(I)
Rules
2-Players, each has 15 pawns on board
Roll dice to move pawns, which could capture opponent's
pawns
Move all of 15 pawns off board to win
Mechanics
Betting/Wagering
Roll/Spin and Move

7. Study of Backgammon(II)
Expectiminimax Tree
Perfect, but incomplete information
Introduce ‘chance node’, takes a weighted
average
Tree <- Min, Max and Chance Node
More about Minimax, Alpha-beta pruning and
expectiminimax tree.

8. Future Discussion
Some other games with ‘chance’:
The Settlers of Catan
The Castles of Burgundy
Using ‘chance’ to produce resources
Could expectiminimax tree be used on the games?

9. American-style vs
German-style(I)
American-style Board Game(also referred to as Ameritrash):
Feature a prominent theme
Encourage direct conflict between players
Have a significant degree of luck
Some classic titles:
Risk
Twilight Imperium(Third Edition)
Betrayal at House on the Hill

10. American-style vs
German-style(II)
German-style Board Game(Aka Eurogame):
Merely mnemonic theme
Family strategy
Low randomness
No player elimination
Some classic titles:
Puerto Rico, Carcassonne
Through the Ages, Terra Mystica

11. American-style vs
German-style(III)
How to implement AI for those styles?
Ameritrash
All the rules are more or less like Backgammon
AI for Risk: Traditional heuristic, MCTS
Euro
Different mechanics(which may mentioned below) make
things different and difficult
AI for Catan: MCTS (imperfect -> perfect, without trading)

12. Popular Card Games(I)
Texas Hold’em (Aka Poker)
Betting/Wagering, Player Elimination
Set Collection, Bluffing
Landlord
Auction/Bidding, Betting/Wagering
Hand Management, Partnerships

13. Popular Card Games(II)
Mahjong
Hand Management, Set Collection
Draw and Discard Games
Bridge
Auction/Bidding, Hand Management
Partnerships, Trick-taking

14. Mechanics(I):
Auction/Bidding
Auction/Bidding
Place a bid to enhance the position of the game
Typical Games: Modern Art
Auction Types: Traditional/Vickery/English/Dutch
Theory: Auction Theory
Research on Bidding Hex Game

15. Mechanics(II):
Betting/Wagering
Betting/Wagering
Encourage or require players to bet money or
certain outcomes within the game.
Typical Games: Wizard
Theory: Gambling and Information Theory

16. Mechanics(III): Bluffing
Bluffing
Hidden Information
Encourage players to use deception to achieve
their aims
Typical Games: Liar’s Dice
Libratus and DeepStack

17. Mechanics(IV): Draw and
Discard
Draw and Discard
Hands, drawing deck and discard pile
Draw and discard to improve your hand towards
some objective
Typical Games: Love Letter, Rummikub
Hand Evaluation: A Mahjong example, Mahjong
with MCTS and opponent Modeling

18. Mechanics(V): Hand
Management
Hand Management
Reward players for playing the cards in certain
sequences or groups
Manage your hands means gaining the most value
out of available cards under given circumstance
Typical Games: Agricola

19. Mechanics(VI):
Partnerships
Partnerships
Offer players a set of rules for alliances and
teams
Often able to win as a team, or penalties are
enforced for not respecting alliances
Typical Games: Tichu, Codenames

20. Mechanics(VII): Player
Elimination
Player Elimination
Multiple-player games(>2) when a player can be
eliminated from the game and play continues without
the eliminated player.
Doesn’t include 2-player-only games where the goal is
to defeat the opponent, e.g, Chess
Typical Games: SanguoSha

21. Mechanics(VIII): Set
Collection
Set Collection
Encourage players to collect a set of items
Typical Games: Ticket to Ride

22. Mechanics(IX): Trick-
taking
Trick-taking
Each player plays in turn order one card(or, in
some games, a series, such as a pair or straight)
from their hands face up onto the table; the
group of cards played is named a ‘trick’. Winner
captures all cards of the trick
Typical Games: Hearts

23. Tea break: Spyfall

24. Family and Party
Games(I)
Spyfall
Setup: Same place, each player except the spy
knows where it is, while the spy knows nothing
Play: QA/Call for voting/Guess(spy)/Vote
Winning condition
Spy: guess the correct place, or survive at last
Others: figure out the spy

25. Family and Party
Games(II)
The Werewolves of Miller’s Hollow
Werewolves: Pretend to be villagers and kill all
the villager at night
Villager: Figure out all the werewolves
Special abilities

26. Family and Party
Games(III)
Dixit
Using phrases to describe pictures
Pretend to be the original picture which matches
the phrase best
Guess

27. HowTo?
NLP
Deduction
Hidden information
Bluffing
GAN
Player portait

28. Thank you!