"Hunt Takes Hare": Theming Games Through Game-Word Vector Translation

TL;DR

This paper introduces a method that links game embeddings with word embeddings to better understand and manipulate game themes, enabling automated thematic translation and reasoning.

Contribution

It presents two approaches for integrating game and word embeddings, demonstrating improved semantic translation of game themes and opening new avenues for thematic analysis.

Findings

Game embeddings improve thematic translation accuracy.

The proposed methods enable automated reasoning about game themes.

Enhanced semantic understanding of game concepts through embedding integration.

Abstract

A game's theme is an important part of its design -- it conveys narrative information, rhetorical messages, helps the player intuit strategies, aids in tutorialisation and more. Thematic elements of games are notoriously difficult for AI systems to understand and manipulate, however, and often rely on large amounts of hand-written interpretations and knowledge. In this paper we present a technique which connects game embeddings, a recent method for modelling game dynamics from log data, and word embeddings, which models semantic information about language. We explain two different approaches for using game embeddings in this way, and show evidence that game embeddings enhance the linguistic translations of game concepts from one theme to another, opening up exciting new possibilities for reasoning about the thematic elements of games in the future.