Loading…

Context-Awareness and Anticipation in a Tennis Video Game AI System

This paper is dedicated to the problem of using case-based reasoning AI in a commercial mobile game of lawn tennis. We discuss the unavoidable manual game analysis stage, aimed to represent user intentions accurately and supply them to the machine learning procedure. We show how the right combinatio...

Full description

Saved in:
Bibliographic Details
Main Author: Mozgovoy, Maxim
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 703
container_issue
container_start_page 699
container_title
container_volume
creator Mozgovoy, Maxim
description This paper is dedicated to the problem of using case-based reasoning AI in a commercial mobile game of lawn tennis. We discuss the unavoidable manual game analysis stage, aimed to represent user intentions accurately and supply them to the machine learning procedure. We show how the right combination of machine learning and manual effort helps to construct a solid game AI system, able to play in human-like manner. Our experience shows that the key factor of the successful decision making and reasonable resource consumption in mobile tennis is careful representation of context-aware behavior and anticipation of opponents' actions, exhibited by real players.
doi_str_mv 10.1109/SMC.2018.00127
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_8616123</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8616123</ieee_id><sourcerecordid>8616123</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-dbf6bb6e02fa6668970a13649ca8676adf767860ffc0e7dcb2d11c2fb94c01aa3</originalsourceid><addsrcrecordid>eNotzsFKw0AQgOFVEGyrVy9e9gUSZzbJ7OYYgtZCxUOr1zJJZmHFbEo3oH17BT39t49fqTuEHBHqh91LmxtAlwOgsRdqiVXhiKgCc6kWprI2Q6qqa7VM6QPAQIluodp2irN8z1nzxSeJkpLmOOgmzqEPR57DFHWImvVeYgxJv4dBJr3mUXSz0btzmmW8UVeeP5Pc_nel3p4e9-1ztn1db9pmmwW01ZwNnaeuIwHj-ffL1RYYCyrrnh1Z4sFbso7A-x7EDn1nBsTe-K4ue0DmYqXu_9wgIofjKYx8Oh8cIaEpih8K3Ujp</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Context-Awareness and Anticipation in a Tennis Video Game AI System</title><source>IEEE Xplore All Conference Series</source><creator>Mozgovoy, Maxim</creator><creatorcontrib>Mozgovoy, Maxim</creatorcontrib><description>This paper is dedicated to the problem of using case-based reasoning AI in a commercial mobile game of lawn tennis. We discuss the unavoidable manual game analysis stage, aimed to represent user intentions accurately and supply them to the machine learning procedure. We show how the right combination of machine learning and manual effort helps to construct a solid game AI system, able to play in human-like manner. Our experience shows that the key factor of the successful decision making and reasonable resource consumption in mobile tennis is careful representation of context-aware behavior and anticipation of opponents' actions, exhibited by real players.</description><identifier>EISSN: 2577-1655</identifier><identifier>EISBN: 1538666502</identifier><identifier>EISBN: 9781538666500</identifier><identifier>DOI: 10.1109/SMC.2018.00127</identifier><identifier>CODEN: IEEPAD</identifier><language>eng</language><publisher>IEEE</publisher><subject>case-based reasoning ; Cognition ; Decision making ; game AI ; Games ; Land mobile radio ; Machine learning ; mobile tennis ; Sports</subject><ispartof>2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018, p.699-703</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8616123$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,23930,23931,25140,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8616123$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mozgovoy, Maxim</creatorcontrib><title>Context-Awareness and Anticipation in a Tennis Video Game AI System</title><title>2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)</title><addtitle>SMC</addtitle><description>This paper is dedicated to the problem of using case-based reasoning AI in a commercial mobile game of lawn tennis. We discuss the unavoidable manual game analysis stage, aimed to represent user intentions accurately and supply them to the machine learning procedure. We show how the right combination of machine learning and manual effort helps to construct a solid game AI system, able to play in human-like manner. Our experience shows that the key factor of the successful decision making and reasonable resource consumption in mobile tennis is careful representation of context-aware behavior and anticipation of opponents' actions, exhibited by real players.</description><subject>case-based reasoning</subject><subject>Cognition</subject><subject>Decision making</subject><subject>game AI</subject><subject>Games</subject><subject>Land mobile radio</subject><subject>Machine learning</subject><subject>mobile tennis</subject><subject>Sports</subject><issn>2577-1655</issn><isbn>1538666502</isbn><isbn>9781538666500</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2018</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotzsFKw0AQgOFVEGyrVy9e9gUSZzbJ7OYYgtZCxUOr1zJJZmHFbEo3oH17BT39t49fqTuEHBHqh91LmxtAlwOgsRdqiVXhiKgCc6kWprI2Q6qqa7VM6QPAQIluodp2irN8z1nzxSeJkpLmOOgmzqEPR57DFHWImvVeYgxJv4dBJr3mUXSz0btzmmW8UVeeP5Pc_nel3p4e9-1ztn1db9pmmwW01ZwNnaeuIwHj-ffL1RYYCyrrnh1Z4sFbso7A-x7EDn1nBsTe-K4ue0DmYqXu_9wgIofjKYx8Oh8cIaEpih8K3Ujp</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Mozgovoy, Maxim</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201810</creationdate><title>Context-Awareness and Anticipation in a Tennis Video Game AI System</title><author>Mozgovoy, Maxim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-dbf6bb6e02fa6668970a13649ca8676adf767860ffc0e7dcb2d11c2fb94c01aa3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2018</creationdate><topic>case-based reasoning</topic><topic>Cognition</topic><topic>Decision making</topic><topic>game AI</topic><topic>Games</topic><topic>Land mobile radio</topic><topic>Machine learning</topic><topic>mobile tennis</topic><topic>Sports</topic><toplevel>online_resources</toplevel><creatorcontrib>Mozgovoy, Maxim</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mozgovoy, Maxim</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Context-Awareness and Anticipation in a Tennis Video Game AI System</atitle><btitle>2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)</btitle><stitle>SMC</stitle><date>2018-10</date><risdate>2018</risdate><spage>699</spage><epage>703</epage><pages>699-703</pages><eissn>2577-1655</eissn><eisbn>1538666502</eisbn><eisbn>9781538666500</eisbn><coden>IEEPAD</coden><abstract>This paper is dedicated to the problem of using case-based reasoning AI in a commercial mobile game of lawn tennis. We discuss the unavoidable manual game analysis stage, aimed to represent user intentions accurately and supply them to the machine learning procedure. We show how the right combination of machine learning and manual effort helps to construct a solid game AI system, able to play in human-like manner. Our experience shows that the key factor of the successful decision making and reasonable resource consumption in mobile tennis is careful representation of context-aware behavior and anticipation of opponents' actions, exhibited by real players.</abstract><pub>IEEE</pub><doi>10.1109/SMC.2018.00127</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier EISSN: 2577-1655
ispartof 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018, p.699-703
issn 2577-1655
language eng
recordid cdi_ieee_primary_8616123
source IEEE Xplore All Conference Series
subjects case-based reasoning
Cognition
Decision making
game AI
Games
Land mobile radio
Machine learning
mobile tennis
Sports
title Context-Awareness and Anticipation in a Tennis Video Game AI System
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-19T16%3A41%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Context-Awareness%20and%20Anticipation%20in%20a%20Tennis%20Video%20Game%20AI%20System&rft.btitle=2018%20IEEE%20International%20Conference%20on%20Systems,%20Man,%20and%20Cybernetics%20(SMC)&rft.au=Mozgovoy,%20Maxim&rft.date=2018-10&rft.spage=699&rft.epage=703&rft.pages=699-703&rft.eissn=2577-1655&rft.coden=IEEPAD&rft_id=info:doi/10.1109/SMC.2018.00127&rft.eisbn=1538666502&rft.eisbn_list=9781538666500&rft_dat=%3Cieee_CHZPO%3E8616123%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-dbf6bb6e02fa6668970a13649ca8676adf767860ffc0e7dcb2d11c2fb94c01aa3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=8616123&rfr_iscdi=true