{"title":"建模和仿真框架的真实城市和棋盘游戏,以培养玩家","authors":"J. Vaccaro","doi":"10.1109/CIG.2009.5286508","DOIUrl":null,"url":null,"abstract":"This tutorial will include: (1) a modeling approach for generating an urban terrain model from a Compact Terrain DataBase (CTDB) for computer-simulation of an urban search and rescue operation (US&RO), (2) a modeling approach for implementing the game RISK and generating autonomous players (3) a generalized implementation strategy for integrating both models into an autonomous dynamic planning and execution (ADP&E) framework for gaming simulations, and (4) an evolutionary strategy for using autonomous simulation results to improve player's abilities. The game RISK a multi-player non-cooperative stochastic game problem, and the US&RO simulation is a single-player multi-agent cooperative game problem. Accumulated results from both applications have given insight into a more general framework to ADP&E for Very Large Partially Observable and Uncertain Environments. The generalization of this approach will be described in terms of its hierarchy, modular components, and dynamic processes.","PeriodicalId":358795,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence and Games","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling and simulation framework of real urban and board games to train players\",\"authors\":\"J. Vaccaro\",\"doi\":\"10.1109/CIG.2009.5286508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This tutorial will include: (1) a modeling approach for generating an urban terrain model from a Compact Terrain DataBase (CTDB) for computer-simulation of an urban search and rescue operation (US&RO), (2) a modeling approach for implementing the game RISK and generating autonomous players (3) a generalized implementation strategy for integrating both models into an autonomous dynamic planning and execution (ADP&E) framework for gaming simulations, and (4) an evolutionary strategy for using autonomous simulation results to improve player's abilities. The game RISK a multi-player non-cooperative stochastic game problem, and the US&RO simulation is a single-player multi-agent cooperative game problem. Accumulated results from both applications have given insight into a more general framework to ADP&E for Very Large Partially Observable and Uncertain Environments. The generalization of this approach will be described in terms of its hierarchy, modular components, and dynamic processes.\",\"PeriodicalId\":358795,\"journal\":{\"name\":\"2009 IEEE Symposium on Computational Intelligence and Games\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Symposium on Computational Intelligence and Games\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIG.2009.5286508\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Symposium on Computational Intelligence and Games","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIG.2009.5286508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and simulation framework of real urban and board games to train players
This tutorial will include: (1) a modeling approach for generating an urban terrain model from a Compact Terrain DataBase (CTDB) for computer-simulation of an urban search and rescue operation (US&RO), (2) a modeling approach for implementing the game RISK and generating autonomous players (3) a generalized implementation strategy for integrating both models into an autonomous dynamic planning and execution (ADP&E) framework for gaming simulations, and (4) an evolutionary strategy for using autonomous simulation results to improve player's abilities. The game RISK a multi-player non-cooperative stochastic game problem, and the US&RO simulation is a single-player multi-agent cooperative game problem. Accumulated results from both applications have given insight into a more general framework to ADP&E for Very Large Partially Observable and Uncertain Environments. The generalization of this approach will be described in terms of its hierarchy, modular components, and dynamic processes.