Adversarial Search in Three Games

Playable browser implementations of the three games from Assignment 2: Quoridor, Ghosts, and UNO. Each game ships with a simple AI opponent that mirrors the algorithms suggested in the assignment notebooks.

Pick a game

Quoridor

9x9 board · 2 players · 10 walls each

Perfect-information, deterministic 2-player game. AI uses BFS shortest-path and a path-difference heuristic with shallow minimax.

Minimax Alpha-beta BFS heuristic

Ghosts

6x6 board · hidden ghost types · setup + play phases

Imperfect-information 2-player game. AI reasons about hidden ghost identities probabilistically, with a setup strategy and capture/exit evaluation.

Expectiminimax Hidden info Belief state

UNO (4-player)

108-card deck · Skip / Reverse / Draw2 / Wild / Wild+4

Imperfect-information multi-agent game. AI uses a rule-based / greedy heuristic that values action cards and tracks the discard pile.

Greedy policy Card counting Stochastic

How this maps to the assignment

Class concepts demonstrated

Search

BFS for shortest path (Quoridor), minimax tree expansion with depth-limited evaluation (Quoridor & Ghosts).

Adversarial & stochastic games

Two-player zero-sum reasoning (Quoridor), expectimax-style averaging over hidden ghost identities (Ghosts), chance nodes from card draws (UNO).

Heuristic design

Path-length differential, mobility, advancement-to-goal, action-card value, hand-size pressure on opponents.