عنوان

Predicting and Enhancing Hearthstone Strategy with Combinatorial Fusion

Number

TLpq2457718890

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Predicting and Enhancing Hearthstone Strategy with Combinatorial Fusion

General Material Designation

[Thesis]

First Statement of Responsibility

Gorelick, Henry William

Subsequent Statement of Responsibility

Hsu, D. F.

Name of Publisher, Distributor, etc.

Fordham University

Date of Publication, Distribution, etc.

2020

Specific Material Designation and Extent of Item

62

Dissertation or thesis details and type of degree

M.S.

Body granting the degree

Fordham University

Text preceding or following the note

2020

Text of Note

The goal of this master's thesis is to demonstrate that combinatorial fusion analysis (CFA) can effectively predict winners and enhance play strategy of Blizzard Entertainment's collectible card game Hearthstone. CFA is used to combine and evaluate the performance of the combinatorial combinations of five machine learning models trained on 500 Hearthstone game simulations. For each combinatorial combination, the score function of the score combination and the score function of the rank combination is derived for each of the five models, and the performance of each is compared and evaluated. The improvement in performance of certain combinations over the individual components validates that CFA is an effective method for predicting the winner of Hearthstone games and enhancing play strategy. Furthermore, the resulting models could be used to boost Monte Carlo Tree Search and implement a competitive Hearthstone playing AI agent.

Artificial intelligence

Arts management

Computer engineering

Computer science

Design

Gorelick, Henry William

Hsu, D. F.

Electronic name

p

[Thesis]

276903

a

Y