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Friends Forever: Social Relationships with a Fuzzy Agent-Based Model Samer Hassan Mauricio Salgado Juan Pav ó n Universidad Complutense de Madrid University of Surrey
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Samer Hassan HAIS08 2008 2 Contents Understanding Friendship Dynamics The ABM Mentat Fuzzification process Results Conclusions
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Samer Hassan HAIS08 2008 3 Understanding Friendship Dynamics “Meeting” & “Mating”: strangers => acquaintances => friends => partner “Meeting”: depends on opportunities alone space & time “Mating”: depends on both opportunities & attraction
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Samer Hassan HAIS08 2008 4 Understanding Friendship Dynamics Proximity principle: The more similar two individuals are, the stronger their chances of becoming friends Features channel individual preferences Homogeneous friendship choices
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Samer Hassan HAIS08 2008 5 Contents Understanding Friendship Dynamics The ABM Mentat Fuzzification process Results Conclusions
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Samer Hassan HAIS08 2008 6 The ABM Mentat Aim: simulate the process of change in moral values in a period in a society Plenty of factors involved Now focusing on demography
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Samer Hassan HAIS08 2008 7 Mentat: architecture Agent: Mental State attributes Life cycle patterns Demographic micro-evolution: Couples Reproduction Inheritance
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Samer Hassan HAIS08 2008 8 Mentat: architecture World: 3000 agents Grid 100x100 Demographic model Network: Communication with Moore Neighbourhood Friends network Family network
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Samer Hassan HAIS08 2008 9 Mentat: Relationships Meeting Agents randomly distributed in space Mating Similarity operator => Boolean friendship Matchmaking Couple chosen among “ candidates ” Quantity? The more friends, the more couples Quality? Couples should be similar
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Samer Hassan HAIS08 2008 10 Mentat: Relationships Meeting Agents randomly distributed in space Mating Similarity operator => Friendship Matchmaking Couple chosen among “ candidates ” Quantity? The more friends, the more couples Quality? Couples should be similar
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Samer Hassan HAIS08 2008 16
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Samer Hassan HAIS08 2008 17 Contents Understanding Friendship Dynamics The ABM Mentat Fuzzification process Results Conclusions
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Samer Hassan HAIS08 2008 18 Be Fuzzy, my Friend Similar, Friend: fuzzy concepts Fuzzification Improve accuracy of similarity Improve realism of friendship Improve quality couples
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Samer Hassan HAIS08 2008 19 Fuzzy Similarity Fuzzifying variables μ economy :U → [0,1] μ economy (ind) = 0.7 Fuzzifying Similarity operator
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Samer Hassan HAIS08 2008 20 Fuzzy Friendship Boolean => Fuzzy relationship But friendship occurs through time: Dynamic evolution! Hypothesis: Logistic function
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Samer Hassan HAIS08 2008 21 Fuzzy Friendship Evolution
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Samer Hassan HAIS08 2008 22 Couples Couple relationship cannot be fuzzified But process improved: Accuracy of similarity New info: friendship
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Samer Hassan HAIS08 2008 23 Contents Understanding Friendship Dynamics The ABM Mentat Fuzzification process Results Conclusions
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Samer Hassan HAIS08 2008 24 Results Implementations (FS, FF): FS: attributes & similarity fuzzified FF: friendship fuzzified, evolving & affecting partner choice Configurations: RND-Fr: promoting random friends (agents can be linked to a non-similar neighbour) SIM-Fr: promoting similarity-based friends (agents will give priority to the most similar neighbours)
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Samer Hassan HAIS08 2008 25 Results
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Samer Hassan HAIS08 2008 26 Contents Understanding Friendship Dynamics The ABM Mentat Fuzzification process Results Conclusions
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Samer Hassan HAIS08 2008 27 Conclusions Fuzzification fits well in social processes Achieved improvements in Accuracy of similarity Realism of friendship Continuous Evolving Quality of the couples Future work Stability of friendship Weak links
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Samer Hassan HAIS08 2008 28 Thanks for your attention! Samer Hassan samer@fdi.ucm.es Universidad Complutense de Madrid University of Surrey
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Samer Hassan HAIS08 2008 29 Contents License This presentation is licensed under a Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/ You are free to copy, modify and distribute it as long as the original work and author are cited
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