Available at: https://digitalcommons.calpoly.edu/theses/3031
Date of Award
6-2025
Degree Name
MS in Statistics
Department/Program
Statistics
College
College of Science and Mathematics
Advisor
Kevin Ross
Advisor Department
Statistics
Advisor College
College of Science and Mathematics
Abstract
This work provides a probability-based analysis of strategies in the board game Ecosystem. Ecosystem is a turn-based multiplayer tiling game, where players take turns picking a wildlife card from a limited pool of cards then placing that card on their personal 4x5 grid. The objective of the game is to place the wildlife cards to maximize your score, as each card’s scoring condition depends on the presence or absence of certain cards surrounding it. The goal of this project is to determine optimal strategies for tiling your grid using techniques such as simulation to find optimal grid arrangements and clustering to examine commonalities in card placements and selection within a grid. This work includes several processes for investigating strategies. For grid simulation, a function for generating and placing cards randomly in a grid and a scoring function for a modified single player version of the game was made. For grid arrangement, a Markov Chain Monte Carlo simulation with a tuned accelerated acceptance function to discover the optimal arrangement of a grid to maximize scoring was utilized. For grid pattern analysis, a large numbers of grids with maximized scores were generated and clustered using K-means clustering to identify possible patterns in card placements and selection. And for strategy inferences, multiple graphical and tabular results to display and compare various aspects of possible winning strategies were created.