链接:人工智能与互动娱乐

R. Amant, R. Young
{"title":"链接:人工智能与互动娱乐","authors":"R. Amant, R. Young","doi":"10.1145/378116.378120","DOIUrl":null,"url":null,"abstract":"A s John Laird pointed out in his IAAI/AAAI invited talk last year, artificial intelligence (AI) research and computer gaming have quite a bit to offer each other. Although many commercially successful computer games have been rather vis-ceral and violent, AI techniques offer the promise of creating engaging and dynamic interactive entertainment with strong narrative components. For AI researchers working in the context of computer games, research challenges are as complex and compelling as many real-world problem areas; gaming environments offer unique interfaces and modes of use and an extensive existing base of potential users. In this article, we introduce some aspects of the application of artificial intelligence research to interactive entertainment. Although intelligent techniques certainly apply to a wide range of computer games, here we will focus on games that simulate or create highly interactive virtual envi-ronments—games in which one or more users control various aspects of the game's world, either in discrete steps (for example, turn-taking) or in continuous real-time modes. These kinds of computer games are excellent environments for artificial intelligence researchers to explore for several reasons. First, as testbeds for AI systems computer games provide a unique combination of simulation and reality. That is, the environment in which a computer game user interacts is virtual, but that environment is not a simulation of the problem domain; it is the problem domain. As a result, AI researchers can choose to side-step issues such as noisy sensor data, imperfect effectors, or other complications often found in real-world problems and still address realistic problems in the game environment. Second, gaming environments pose a range of problems, at both the strategic and interface levels. Strategic-level challenges in computer games can involve mapping or choosing between complex strategies, refining components of a strategy by formulating context-specific move sequences, and detecting and responding to human users' actions. At the interface level, intelligent components inside a game must control how the game world is presented to the users. Perhaps a unique property of 3-D game environments is that, in many aspects, they are their own interface. That is, every aspect of a game's virtual e n v i r o n m e n t — i t s objects, characters, lighting , sound, and camera— can be exploited by the system to create an overall effective interaction. Recent research has addressed many of the issues at the interface level (for example, the …","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"39 1","pages":"17-19"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Links: artificial intelligence and interactive entertainment\",\"authors\":\"R. Amant, R. Young\",\"doi\":\"10.1145/378116.378120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A s John Laird pointed out in his IAAI/AAAI invited talk last year, artificial intelligence (AI) research and computer gaming have quite a bit to offer each other. Although many commercially successful computer games have been rather vis-ceral and violent, AI techniques offer the promise of creating engaging and dynamic interactive entertainment with strong narrative components. For AI researchers working in the context of computer games, research challenges are as complex and compelling as many real-world problem areas; gaming environments offer unique interfaces and modes of use and an extensive existing base of potential users. In this article, we introduce some aspects of the application of artificial intelligence research to interactive entertainment. Although intelligent techniques certainly apply to a wide range of computer games, here we will focus on games that simulate or create highly interactive virtual envi-ronments—games in which one or more users control various aspects of the game's world, either in discrete steps (for example, turn-taking) or in continuous real-time modes. These kinds of computer games are excellent environments for artificial intelligence researchers to explore for several reasons. First, as testbeds for AI systems computer games provide a unique combination of simulation and reality. That is, the environment in which a computer game user interacts is virtual, but that environment is not a simulation of the problem domain; it is the problem domain. As a result, AI researchers can choose to side-step issues such as noisy sensor data, imperfect effectors, or other complications often found in real-world problems and still address realistic problems in the game environment. Second, gaming environments pose a range of problems, at both the strategic and interface levels. Strategic-level challenges in computer games can involve mapping or choosing between complex strategies, refining components of a strategy by formulating context-specific move sequences, and detecting and responding to human users' actions. At the interface level, intelligent components inside a game must control how the game world is presented to the users. Perhaps a unique property of 3-D game environments is that, in many aspects, they are their own interface. That is, every aspect of a game's virtual e n v i r o n m e n t — i t s objects, characters, lighting , sound, and camera— can be exploited by the system to create an overall effective interaction. Recent research has addressed many of the issues at the interface level (for example, the …\",\"PeriodicalId\":8272,\"journal\":{\"name\":\"Appl. Intell.\",\"volume\":\"39 1\",\"pages\":\"17-19\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Appl. Intell.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/378116.378120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Appl. Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/378116.378120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

正如John Laird在去年的IAAI/AAAI邀请演讲中指出的那样,人工智能(AI)研究和电脑游戏可以相互提供很多东西。尽管许多商业上成功的电脑游戏都带有视觉和暴力元素,但AI技术却能够创造出具有强大叙事元素的引人入胜的动态互动娱乐。对于在电脑游戏背景下工作的AI研究人员来说,研究挑战与许多现实世界的问题领域一样复杂和引人注目;游戏环境提供了独特的界面和使用模式以及广泛的现有潜在用户基础。在本文中,我们介绍了人工智能研究在互动娱乐中的一些应用。虽然智能技术确实适用于广泛的电脑游戏,但在这里,我们将重点关注模拟或创造高度互动的虚拟环境的游戏——在这些游戏中,一个或多个用户可以控制游戏世界的各个方面,或者是在离散的步骤中(例如,轮流),或者是在连续的实时模式中。这类电脑游戏是人工智能研究人员探索的绝佳环境,原因如下。首先,作为人工智能系统的测试平台,电脑游戏提供了模拟与现实的独特结合。也就是说,电脑游戏用户互动的环境是虚拟的,但该环境不是问题域的模拟;它是问题域。因此,AI研究人员可以选择回避诸如嘈杂的传感器数据、不完美的效应器或其他在现实世界问题中经常出现的复杂性等问题,而仍然可以解决游戏环境中的现实问题。其次,游戏环境在策略和界面层面上都存在一系列问题。电脑游戏中的策略层面挑战包括映射或选择复杂的策略,通过制定特定情境的移动序列来完善策略的组成部分,以及检测和响应人类用户的行动。在界面层面,游戏中的智能组件必须控制游戏世界呈现给用户的方式。也许3d游戏环境的一个独特属性是,在许多方面,它们都是自己的界面。也就是说,游戏虚拟世界的方方面面都可以被系统利用,包括物体、角色、灯光、声音和镜头等,从而创造出整体有效的互动效果。最近的研究已经解决了接口级别的许多问题(例如,…
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Links: artificial intelligence and interactive entertainment
A s John Laird pointed out in his IAAI/AAAI invited talk last year, artificial intelligence (AI) research and computer gaming have quite a bit to offer each other. Although many commercially successful computer games have been rather vis-ceral and violent, AI techniques offer the promise of creating engaging and dynamic interactive entertainment with strong narrative components. For AI researchers working in the context of computer games, research challenges are as complex and compelling as many real-world problem areas; gaming environments offer unique interfaces and modes of use and an extensive existing base of potential users. In this article, we introduce some aspects of the application of artificial intelligence research to interactive entertainment. Although intelligent techniques certainly apply to a wide range of computer games, here we will focus on games that simulate or create highly interactive virtual envi-ronments—games in which one or more users control various aspects of the game's world, either in discrete steps (for example, turn-taking) or in continuous real-time modes. These kinds of computer games are excellent environments for artificial intelligence researchers to explore for several reasons. First, as testbeds for AI systems computer games provide a unique combination of simulation and reality. That is, the environment in which a computer game user interacts is virtual, but that environment is not a simulation of the problem domain; it is the problem domain. As a result, AI researchers can choose to side-step issues such as noisy sensor data, imperfect effectors, or other complications often found in real-world problems and still address realistic problems in the game environment. Second, gaming environments pose a range of problems, at both the strategic and interface levels. Strategic-level challenges in computer games can involve mapping or choosing between complex strategies, refining components of a strategy by formulating context-specific move sequences, and detecting and responding to human users' actions. At the interface level, intelligent components inside a game must control how the game world is presented to the users. Perhaps a unique property of 3-D game environments is that, in many aspects, they are their own interface. That is, every aspect of a game's virtual e n v i r o n m e n t — i t s objects, characters, lighting , sound, and camera— can be exploited by the system to create an overall effective interaction. Recent research has addressed many of the issues at the interface level (for example, the …
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Object interaction-based surveillance video synopsis Total generalized variational-liked network for image denoising Multi-level clustering based on cluster order constructed with dynamic local density Natural-language processing for computer-supported instruction Is AI abstract and impractical? isn't the answer obvious?
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1