Date of Award
5-2022
Document Type
Thesis campus only
Department
Computer Science
First Advisor
Britton Horn
Second Advisor
Sheng Tan
Abstract
Generating decks in Collectible Card Games (CCG’s) has been a hot spot for artificial intelligence in recent years. Artificial intelligence methods have usually attacked this problem without considering the specific cards accessible to a player. In this paper, we examine the capability to generate decks in Hearthstone, a CCG, for individual players based on their cards using Evolutionary Algorithms (EA) with a neural network fitness function. In these experiments, the approach shows a promising result that EA algorithms can generate good decks for a players collection.
Recommended Citation
Young, Douglas, "Generating the Best Hearthstone Decks for a Players Collection via Artificial Intelligence" (2022). Computer Science Honors Theses. 63.
https://digitalcommons.trinity.edu/compsci_honors/63