{"title":"学会在人群中移动","authors":"Jaedong Lee, Jehee Lee","doi":"10.1145/3230744.3230782","DOIUrl":null,"url":null,"abstract":"The main goal of the crowd simulation is to generate realistic movements of agents. Reproducing the mechanism that seeing the environments, understanding current situation, and deciding where to step is crucial point to simulating crowd movements. We formulate the process of walking mechanism using deep reinforcement learning. And we experiment some typical scenarios.","PeriodicalId":226759,"journal":{"name":"ACM SIGGRAPH 2018 Posters","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Learning to move in crowd\",\"authors\":\"Jaedong Lee, Jehee Lee\",\"doi\":\"10.1145/3230744.3230782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main goal of the crowd simulation is to generate realistic movements of agents. Reproducing the mechanism that seeing the environments, understanding current situation, and deciding where to step is crucial point to simulating crowd movements. We formulate the process of walking mechanism using deep reinforcement learning. And we experiment some typical scenarios.\",\"PeriodicalId\":226759,\"journal\":{\"name\":\"ACM SIGGRAPH 2018 Posters\",\"volume\":\"128 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SIGGRAPH 2018 Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3230744.3230782\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGGRAPH 2018 Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3230744.3230782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The main goal of the crowd simulation is to generate realistic movements of agents. Reproducing the mechanism that seeing the environments, understanding current situation, and deciding where to step is crucial point to simulating crowd movements. We formulate the process of walking mechanism using deep reinforcement learning. And we experiment some typical scenarios.
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