{"title":"注意作为行动的选择:一种主动感知的方案","authors":"C. Balkenius, Nils Hulth","doi":"10.1109/EURBOT.1999.827629","DOIUrl":null,"url":null,"abstract":"Proposes three principles for attentional control of actions in autonomous robots. (1) Attention-as-action suggests that attentional shifts and the selection of the focus of attention should be seen as actions rather than as a purely sensory process. (2) Selection-for-action suggests that actions should be implicitly controlled by the current focus of attention. (3) Deictic reference is a method of referring to an external object without explicitly representing all of its properties. The three principles are illustrated in two examples: first for a mobile robot, and second for a visually controlled manipulator. In the second example, we also report two learning experiments where a robot picks out the correct focus of attention for a task based on reinforcement learning.","PeriodicalId":364500,"journal":{"name":"1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Attention as selection-for-action: a scheme for active perception\",\"authors\":\"C. Balkenius, Nils Hulth\",\"doi\":\"10.1109/EURBOT.1999.827629\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Proposes three principles for attentional control of actions in autonomous robots. (1) Attention-as-action suggests that attentional shifts and the selection of the focus of attention should be seen as actions rather than as a purely sensory process. (2) Selection-for-action suggests that actions should be implicitly controlled by the current focus of attention. (3) Deictic reference is a method of referring to an external object without explicitly representing all of its properties. The three principles are illustrated in two examples: first for a mobile robot, and second for a visually controlled manipulator. In the second example, we also report two learning experiments where a robot picks out the correct focus of attention for a task based on reinforcement learning.\",\"PeriodicalId\":364500,\"journal\":{\"name\":\"1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EURBOT.1999.827629\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURBOT.1999.827629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Attention as selection-for-action: a scheme for active perception
Proposes three principles for attentional control of actions in autonomous robots. (1) Attention-as-action suggests that attentional shifts and the selection of the focus of attention should be seen as actions rather than as a purely sensory process. (2) Selection-for-action suggests that actions should be implicitly controlled by the current focus of attention. (3) Deictic reference is a method of referring to an external object without explicitly representing all of its properties. The three principles are illustrated in two examples: first for a mobile robot, and second for a visually controlled manipulator. In the second example, we also report two learning experiments where a robot picks out the correct focus of attention for a task based on reinforcement learning.