“Did You Hear That?” Learning to Play Video Games from Audio Cues

Raluca D. Gaina; Matthew Stephenson

doi:10.1109/CIG.2019.8848088

“Did You Hear That?” Learning to Play Video Games from Audio Cues

^*Corresponding author for this work

Advanced Computing Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

Game-playing AI research has focused for a long time on learning to play video games from visual input or symbolic information. However, humans benefit from a wider array of sensors which we utilise in order to navigate the world around us. In particular, sounds and music are key to how many of us perceive the world and influence the decisions we make. In this paper, we present initial experiments on game-playing agents learning to play video games solely from audio cues. We expand the Video Game Description Language to allow for audio specification, and the General Video Game AI framework to provide new audio games and an API for learning agents to make use of audio observations. We analyse the games and the audio game design process, include initial results with simple QLearning agents, and encourage further research in this area.

Original language	English
Title of host publication	IEEE Conference on Games 2019
Publisher	IEEE
Number of pages	4
ISBN (Print)	9781728118840
DOIs	https://doi.org/10.1109/CIG.2019.8848088
Publication status	Published - 2019
Event	IEEE Conference on Games (IEEE COG) - London, United Kingdom Duration: 20 Aug 2019 → 23 Aug 2019 https://ieee-cog.org/2019/

Publication series

Series	IEEE Conference on Computational Intelligence and Games
ISSN	2325-4270

Conference

Conference	IEEE Conference on Games (IEEE COG)
Country/Territory	United Kingdom
City	London
Period	20/08/19 → 23/08/19
Internet address	https://ieee-cog.org/2019/

Access to Document

10.1109/CIG.2019.8848088

Cite this

@inproceedings{9a9f10392d7f4bf28cc3b037e766d8bc,

title = "“Did You Hear That?” Learning to Play Video Games from Audio Cues",

abstract = "Game-playing AI research has focused for a long time on learning to play video games from visual input or symbolic information. However, humans benefit from a wider array of sensors which we utilise in order to navigate the world around us. In particular, sounds and music are key to how many of us perceive the world and influence the decisions we make. In this paper, we present initial experiments on game-playing agents learning to play video games solely from audio cues. We expand the Video Game Description Language to allow for audio specification, and the General Video Game AI framework to provide new audio games and an API for learning agents to make use of audio observations. We analyse the games and the audio game design process, include initial results with simple QLearning agents, and encourage further research in this area.",

author = "Gaina, {Raluca D.} and Matthew Stephenson",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; IEEE Conference on Games (IEEE COG) ; Conference date: 20-08-2019 Through 23-08-2019",

year = "2019",

doi = "10.1109/CIG.2019.8848088",

language = "English",

isbn = "9781728118840",

series = "IEEE Conference on Computational Intelligence and Games",

publisher = "IEEE",

booktitle = "IEEE Conference on Games 2019",

address = "United States",

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T1 - “Did You Hear That?” Learning to Play Video Games from Audio Cues

AU - Gaina, Raluca D.

AU - Stephenson, Matthew

PY - 2019

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N2 - Game-playing AI research has focused for a long time on learning to play video games from visual input or symbolic information. However, humans benefit from a wider array of sensors which we utilise in order to navigate the world around us. In particular, sounds and music are key to how many of us perceive the world and influence the decisions we make. In this paper, we present initial experiments on game-playing agents learning to play video games solely from audio cues. We expand the Video Game Description Language to allow for audio specification, and the General Video Game AI framework to provide new audio games and an API for learning agents to make use of audio observations. We analyse the games and the audio game design process, include initial results with simple QLearning agents, and encourage further research in this area.

AB - Game-playing AI research has focused for a long time on learning to play video games from visual input or symbolic information. However, humans benefit from a wider array of sensors which we utilise in order to navigate the world around us. In particular, sounds and music are key to how many of us perceive the world and influence the decisions we make. In this paper, we present initial experiments on game-playing agents learning to play video games solely from audio cues. We expand the Video Game Description Language to allow for audio specification, and the General Video Game AI framework to provide new audio games and an API for learning agents to make use of audio observations. We analyse the games and the audio game design process, include initial results with simple QLearning agents, and encourage further research in this area.

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DO - 10.1109/CIG.2019.8848088

M3 - Conference article in proceeding

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BT - IEEE Conference on Games 2019

PB - IEEE

T2 - IEEE Conference on Games (IEEE COG)

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