Bio-Inspired Collective Decision Making in Multiagent System: From Low- to High-Cognition Algorithms

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atmire.migration.oldid2095
dc.contributor.advisorLeung, Henry
dc.contributor.authorAichour, Hichem Zakaria
dc.date.accessioned2014-05-14T18:49:06Z
dc.date.available2014-06-16T07:00:44Z
dc.date.issued2014-05-14
dc.date.submitted2014en
dc.description.abstractAt the beginning, this thesis proposes an algorithm inspired by ant's scout-and-recruit for foraging providing a low-cognition algorithm to rescue civilians in distress and explaining how it could be achieved. Being low-cognition algorithm, this algorithm is characterized by having minimal computation and communication between the agents of the MAS as well as being applicable for large scale environment due to its inspiration from ants. Then, an algorithm inspired by human's conformity is provided which is considered a high-cognition algorithm. This algorithm is applied to a rescue mission that is simulated using \emph{RoboCup Rescue Simulator}. Being high-cognition algorithm, this algorithm is characterized by having heavy computation and communication made by the agents of the MAS. Finally, the conformity algorithm is integrated on top of the scout-and-recruit algorithm to enhance its performance. While the low-cognition part insures its applicability to large scale, the high-cognition algorithm pushes the agents to make smarter decisions enhancing the overall system performance.en_US
dc.identifier.citationAichour, H. Z. (2014). Bio-Inspired Collective Decision Making in Multiagent System: From Low- to High-Cognition Algorithms (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25126en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/25126
dc.identifier.urihttp://hdl.handle.net/11023/1520
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectArtificial Intelligence
dc.subjectEngineering--Electronics and Electrical
dc.subjectRobotics
dc.subject.classificationCDMen_US
dc.subject.classificationMASen_US
dc.subject.classificationBio-Inspireden_US
dc.titleBio-Inspired Collective Decision Making in Multiagent System: From Low- to High-Cognition Algorithms
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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