110 likes | 414 Views
Clover Bobker Nikita Kiriy Juan Pablo Sarmiento. King Fish. Fishy fishy. Problem Statement and Motivation. Make an adaptive AI player that can win a game against another “smart” AI. Project Scope: Stage one: pre-programmed AI player. Can beat random player with heuristic move choices.
E N D
Clover Bobker Nikita Kiriy Juan Pablo Sarmiento King Fish Fishy fishy
Problem Statement and Motivation • Make an adaptive AI player that can win a game against another “smart” AI. • Project Scope: • Stage one: pre-programmed AI player. Can beat random player with heuristic move choices. • Stage two: analyzes opponent's strategy real time and adapts to it.
I/O Specification • Inputs: • At the start of game: board layout and obstacles. • Each turn: position of players and any gray markers. • Outputs: • Next move to perform.
Background Reading • Class textbook for high level techniques and design. • Online resources on automated chinese checker players (if available).
Generic Approach • Stage 1: • Rules and heuristic search. • Make AI learn from a dataset of recorded games. • Stage 2: • Create a model of the opponent during the game. Predict opponents moves.
System Architecture and work plan • Independent parts to our system: • Time distribution decision system (limit of 10 minutes) • Learning system that trains off of previous games (Stage 1 AI) • System of rules of the game • Shortest-path finder system to take obstacles into account
Data Sources • Learn from recorded games • Our bots playing themselves • From people (friends) playing with our bot • We would have to design an interface for this
Evaluation Plans • Metrics: • Estimate average time needed per mood and overhead planning time • Make sure memory doesn't crash computer • Improve victory margin (in case of ties) • Test problems: • Give AI prearranged board with a winning strategy composed of several moves. • Simple case: one move. Hard case: increase number of moves. • Make sure AI performs winning sequence of moves each time.