{"title":"Simulation of agent behavior in a goal finding application","authors":"Sharad Sharma, Supriya Lohgaonkar","doi":"10.1109/SECON.2010.5453811","DOIUrl":null,"url":null,"abstract":"There has been increasing interest in simulation of agent behavior in the context of agent based modeling. This paper concentrates on the use of fuzzy logic in simulating agent based behavior. Our approach is decomposed into two levels. The higher level addresses the agent's goal finding behavior and lower level addresses collision detection and avoidance behavior. Our approach focuses on modeling individual behavior as well as group behavior. Individuals constantly adjust their behavior according to the dynamic factors in the environment. We hypothesize that people with similar characteristics such as race, age, and gender are more likely to collaborate with each other in order to reach a goal. This paper describes an agent based system implementation for crowd behavior. The simulation evaluates different evacuation and damage control decision making strategies beforehand, which allows the execution of the most effective evacuation scheme during real-time emergency scenario.","PeriodicalId":286940,"journal":{"name":"Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2010.5453811","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
There has been increasing interest in simulation of agent behavior in the context of agent based modeling. This paper concentrates on the use of fuzzy logic in simulating agent based behavior. Our approach is decomposed into two levels. The higher level addresses the agent's goal finding behavior and lower level addresses collision detection and avoidance behavior. Our approach focuses on modeling individual behavior as well as group behavior. Individuals constantly adjust their behavior according to the dynamic factors in the environment. We hypothesize that people with similar characteristics such as race, age, and gender are more likely to collaborate with each other in order to reach a goal. This paper describes an agent based system implementation for crowd behavior. The simulation evaluates different evacuation and damage control decision making strategies beforehand, which allows the execution of the most effective evacuation scheme during real-time emergency scenario.