DataDriven AgentBased Social Simulation of Moral Values Evolution
Data-Driven Agent-Based Social Simulation of Moral Values Evolution Samer Hassan Universidad Complutense de Madrid University of Surrey
Contents The Problem ABM Mentat: Design ABM Mentat: Results AI: Fuzzy Logic AI: Natural Language Processing AI: Data Mining Samer Hassan SSASA 2008 2
Objective Study the evolution of Spanish society in the period 1980 -2000 Data-Driven Agent-Based Modelling Applying several Artificial Intelligence techniques Samer Hassan SSASA 2008 3
The Problem Aim: simulate the process of change in moral values in a period in a society Plenty of factors involved Nowadays, centred in the inertia of generational change: Samer Hassan To which extent the demographic dynamics explain the mentality change? SSASA 2008 4
The Problem Input Data loaded: EVS-1980 Quantitative periodical info Representative sample of Spain Allows Validation Intra-generational: Samer Hassan Agent characteristics remain constant Macro aggregation evolves SSASA 2008 5
Contents The Problem ABM Mentat: Design ABM Mentat: Results AI: Fuzzy Logic AI: Natural Language Processing AI: Data Mining Samer Hassan SSASA 2008 6
Design of Mentat World: Agent: EVS Agent MS attributes 3000 agents Grid 100 x 100 Life cycle patterns Demographic model Demographic micro-evolution: • Couples • Reproduction • Inheritance Network: Communication with Moore Neighbourhood Friends network Family network Samer Hassan SSASA 2008 7
Friendship Network Samer Hassan SSASA 2008 8
Friendship Network Samer Hassan SSASA 2008 9
Friendship Network Samer Hassan SSASA 2008 10
Friendship Network Samer Hassan SSASA 2008 11
Friendship Network Samer Hassan SSASA 2008 12
Friendship Network Samer Hassan SSASA 2008 13
Friendship Network Samer Hassan SSASA 2008 14
Friendship Network Samer Hassan SSASA 2008 15
Methodological aspects Data-driven ABM Design with qualitative info Microsimulation concepts Life cycle, micro-processes Introduction of empirical equations Life expectancy, birth rate, different probabilities Initialisation with survey data Validation with different empirical data Samer Hassan SSASA 2008 16
Mentat in action Samer Hassan SSASA 2008 17
Contents The Problem ABM Mentat: Design ABM Mentat: Results AI: Fuzzy Logic AI: Natural Language Processing AI: Data Mining Samer Hassan SSASA 2008 18
Results Samer Hassan SSASA 2008 19
Results It may arise new sociological knowledge: Demographic Dynamics are a key factor for the prediction of social trends in Spanish society Samer Hassan SSASA 2008 20
Contents The Problem ABM Mentat: Design ABM Mentat: Results AI: Fuzzy Logic AI: Natural Language Processing AI: Data Mining Samer Hassan SSASA 2008 21
Introduction of AI: Fuzzy Logic Why Fuzzy Logic? Social sciences are characterized by uncertain and vague knowledge Different concept than probability Age Young Adult Old 10 1 0 0 20 0. 8 0. 1 30 0. 5 1 0. 2 40 0. 2 1 0. 4 50 0. 1 1 0. 6 Samer Hassan SSASA 2008 22
Fuzzification Attributes Similarity Friendship & its evolution Couples Samer Hassan SSASA 2008 23
Contents The Problem ABM Mentat: Design ABM Mentat: Results AI: Fuzzy Logic AI: Natural Language Processing AI: Data Mining Samer Hassan SSASA 2008 24
Introduction of AI: NLP Fuzzy logic helps for ABM qualitative input NLP helps for ABM qualitative output Experimenting with life-events generation: Output in natural language: life-story of a representative individual (Ex: hyper-inflation) Applications: NL format makes direct comparison with real stories possible Information very simple for any individual to understand Complementing explanations of quantitative research Samer Hassan SSASA 2008 25
Quantitative & Qualitative Output Generation Samer Hassan SSASA 2008 26
An example: part of the XML output <Log Id="i 49"> <Description /> <Attribute Id="name" Value="rosa" /> <Attribute Id="last_name" Value="pérez" /> <Attribute Id="sex" Value="female" /> <Attribute Id="ideology" Value="left" /> <Attribute Id="education" Value="high" />. . . <Events> <Event Id="e 1" Time="1955" Action="birth" Param="" /> <Event Id="e 2" Time="1960" Action="friend" Param="i 344" /> <Event Id="e 3" Time="1960" Action="friend" Param="i 439" /> <Event Id="e 4" Time="1961" Action="friend" Param="i 151" /> <Event Id="e 5" Time="1962" Action="horrible" Param="childhood" /> <Event Id="e 6" Time="1963" Action="best friend" Param="i 151" /> <Event Id="e 7" Time="1964" Action="believe" Param="god" /> <Event Id="e 8" Time="1964" Action="every week go" Param="church" />. . . <Event Id="e 16" Time="1968" Action="problems" Param="drugs" /> <Event Id="e 17" Time="1971" Action="grow" Param="adult" /> <Event Id="e 18" Time="1971" Action="friend" Param="i 98" /> <Event Id="e 19" Time="1972" Action="involved" Param="labour union" /> <Event Id="e 20" Time="1972" Action="friend" Param="i 156" /> <Event Id="e 21" Time="1973" Action="get" Param="arrested" /> <Event Id="e 22" Time="1973" Action="learn" Param="play guitar" /> <Event Id="e 23" Time="1975" Action="became" Param="hippy" />. . . <Event Id="e 36" Time="1985" Action="divorce" Param="i 439" /> <Event Id="e 37" Time="1987" Action="couple" Param="i 102" /> <Event Id="e 38" Time="1987" Action="live together" Param="i 102" /> <Event Id="e 39" Time="1987" Action="have" Param="abortion" />. . . </Log> <Log Id="i 50"> <Description /> <Attribute Id="name" Value=“francisco" />. . . Samer Hassan SSASA 2008 27
An example: part of the life-story generated Rosa Pérez was born in 1955, and she met Luis Martínez, and she met Miguel López. She suffered a horrible childhood, and she had a very good friend: María Valdés, and she believed in God, and she used to go to church every week. . When she was a teenager, (. . . ) she had problems with drugs, and she became an adult, and she met Marci Boyle, and while she was involved in a labour union, she met Carla González and she got arrested. She learned how to play the guitar, and so she became a hippy, getting involved in a NGO. . She met Sara Hernández, and she stopped going to church, and she met Marcos Torres, and she fell in love, desperately, with Marcos Torres, but in the end she went out with Miguel López, and she co-habitated with Miguel López, and she had a child: Melvin López. . She met Sergio Ruiz, and she separated from Miguel López, and she went out with Sergio Ruiz, and she co-habitated with Sergio Ruiz. She had a abortion, and so she had a depression, and she had a crisis of values. She was unfaithful to Sergio Ruiz with another man. . Nowadays she is an atheist. Samer Hassan SSASA 2008 28
Contents The Problem ABM Mentat: Design ABM Mentat: Results AI: Fuzzy Logic AI: Natural Language Processing AI: Data Mining Samer Hassan SSASA 2008 29
Introduction of AI: Data Mining is the process of extracting patterns and relevant information from large amounts of data Design: Pre-processing of empirical data (surveys): Allows simplification, locates redundant attributes Clustering: selection of qualitative “ideal types” Post-processing of simulation output: Clustering: • Shows non-visible patterns • Comparison of patterns • Different life-stories for each pattern Samer Hassan Classification: evolution of “ideal types” SSASA 2008 30
Limitations & Future Work Enough demography! Quest for a proper cognitive model for this task Overcome methodological limitation: implementing diffusion of moral values . . . or forget about it definitely not BDI Improve other aspects: Samer Hassan ABM design (Ex: friendship ties may weaken) Fuzzy inference Quality of biographies SSASA 2008 31
Thanks for your attention! Samer Hassan samer@fdi. ucm. es Samer Hassan SSASA 2008 32
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 Samer Hassan SSASA 2008 33
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