机器中的幽灵2.0:控制复杂环境的心理仿生步骤

P. Palensky
{"title":"机器中的幽灵2.0:控制复杂环境的心理仿生步骤","authors":"P. Palensky","doi":"10.1109/INDIN.2008.4618052","DOIUrl":null,"url":null,"abstract":"Summary form only given. Technical systems get into serious troubles, once confronted with a certain degree of complexity. An analytical, exhaustive description of a complex problem is often not possible, and so its solution. Far away from scalar control loops and PLC (programmable logic controller) based machinery control, future automation systems are supposed to process a tremendous amount of information coming from millions of sensors and complex information sources like cameras. Large numbers of inexpensive and diverse sources of information can increase the performance of automation tasks in buildings, factories, transport systems, or machinery. However, the complex and context-dependent semantics of such large amounts of data make bit-by-bit processing and traditional rule-based decisions impossible. A new trail from the sensor values to decisions is necessary. Let us take a journey into a new research approach, where bionic systems try to mimic the capabilities of conscious creatures. The human mind, as described in the latest findings of neurology and psychoanalysis, gives a blueprint of a system that is potentially capable of filtering, evaluating, and judging situations and scenarios. The relationship between system/environment interactions, memory, emotions, learning, and higher mental processes is believed to be the key for the success exhibited by our species. This talk will outline the possibilities, the state of the art and the expectations of applying new ideas in artificial intelligence, psychology and neurology in complex industrial automation environments and shall serve as inspiration and challenge to the INDIN community.","PeriodicalId":112553,"journal":{"name":"2008 6th IEEE International Conference on Industrial Informatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The ghost in the machine 2.0: Psycho-bionic steps towards mastering complex environments\",\"authors\":\"P. Palensky\",\"doi\":\"10.1109/INDIN.2008.4618052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. Technical systems get into serious troubles, once confronted with a certain degree of complexity. An analytical, exhaustive description of a complex problem is often not possible, and so its solution. Far away from scalar control loops and PLC (programmable logic controller) based machinery control, future automation systems are supposed to process a tremendous amount of information coming from millions of sensors and complex information sources like cameras. Large numbers of inexpensive and diverse sources of information can increase the performance of automation tasks in buildings, factories, transport systems, or machinery. However, the complex and context-dependent semantics of such large amounts of data make bit-by-bit processing and traditional rule-based decisions impossible. A new trail from the sensor values to decisions is necessary. Let us take a journey into a new research approach, where bionic systems try to mimic the capabilities of conscious creatures. The human mind, as described in the latest findings of neurology and psychoanalysis, gives a blueprint of a system that is potentially capable of filtering, evaluating, and judging situations and scenarios. The relationship between system/environment interactions, memory, emotions, learning, and higher mental processes is believed to be the key for the success exhibited by our species. This talk will outline the possibilities, the state of the art and the expectations of applying new ideas in artificial intelligence, psychology and neurology in complex industrial automation environments and shall serve as inspiration and challenge to the INDIN community.\",\"PeriodicalId\":112553,\"journal\":{\"name\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIN.2008.4618052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 6th IEEE International Conference on Industrial Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2008.4618052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

只提供摘要形式。技术系统一旦面临一定程度的复杂性,就会陷入严重的困境。对一个复杂问题进行分析性的、详尽的描述往往是不可能的,因此它的解决方案也是不可能的。远离标量控制回路和基于PLC(可编程逻辑控制器)的机械控制,未来的自动化系统应该处理来自数百万个传感器和复杂信息源(如相机)的大量信息。大量廉价和多样化的信息来源可以提高建筑物、工厂、运输系统或机械中的自动化任务的性能。然而,如此大量数据的复杂且依赖于上下文的语义使得逐位处理和传统的基于规则的决策变得不可能。从传感器值到决策的新路径是必要的。让我们进入一种新的研究方法,仿生学系统试图模仿有意识生物的能力。正如神经学和精神分析学的最新发现所描述的那样,人类的思想给出了一个系统的蓝图,该系统具有过滤、评估和判断情况和情景的潜在能力。系统/环境相互作用、记忆、情感、学习和高级心理过程之间的关系被认为是人类成功的关键。本次演讲将概述在复杂的工业自动化环境中应用人工智能、心理学和神经学新思想的可能性、现状和期望,并将为INDIN社区提供灵感和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The ghost in the machine 2.0: Psycho-bionic steps towards mastering complex environments
Summary form only given. Technical systems get into serious troubles, once confronted with a certain degree of complexity. An analytical, exhaustive description of a complex problem is often not possible, and so its solution. Far away from scalar control loops and PLC (programmable logic controller) based machinery control, future automation systems are supposed to process a tremendous amount of information coming from millions of sensors and complex information sources like cameras. Large numbers of inexpensive and diverse sources of information can increase the performance of automation tasks in buildings, factories, transport systems, or machinery. However, the complex and context-dependent semantics of such large amounts of data make bit-by-bit processing and traditional rule-based decisions impossible. A new trail from the sensor values to decisions is necessary. Let us take a journey into a new research approach, where bionic systems try to mimic the capabilities of conscious creatures. The human mind, as described in the latest findings of neurology and psychoanalysis, gives a blueprint of a system that is potentially capable of filtering, evaluating, and judging situations and scenarios. The relationship between system/environment interactions, memory, emotions, learning, and higher mental processes is believed to be the key for the success exhibited by our species. This talk will outline the possibilities, the state of the art and the expectations of applying new ideas in artificial intelligence, psychology and neurology in complex industrial automation environments and shall serve as inspiration and challenge to the INDIN community.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信