Agent-Based Simulation in History Research
Using High Performance Computing
Nov., 13, 2009 AESCS2009, Taiwan
Takao TERANO
Department of Computational Intelligencs &
Systems Sciences
Tokyo Institute of Technology
terano@dis.titech.ac.jp
www.trn.dis.titech.ac.jp
One Minute Summary
• Background:
– High Performance Computing
– Computational Social Science
• Motivation:
– Investigate “Past Events” by Rewinding the tape
• Topic We Concern:
– Civil Servant Examination System (科挙試験) in China
over 1,400years
• Approach:
– Data Analysis (Mining!)
– Agent-Based Approaches with Large-scale Optimization
Algorithms & a Grid Environment
• Result:
– “Art is a lie that helps us see reality” by Pablo Picasso
– Also , ABM with High Performance Computing is …
Agenda
•
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•
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•
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Introduction
Computational History Research
Description of Chinese CS Exams
Modeling Genealogical Records to Agents
Optimization of ABS & GOGA Framework
Experimental Results & Findings
Concluding Remarks
TSUBAME Grid at Titech
No 9 from the Data “Top 500 inNov., 2006”
History Research & Archaeology
- The only discipline with the time range to
study long-term culture change.
• Agent based modeling allows us to “rewind
the tape” of cultural evolution.
• Impossible to experiment & to make
verification difficult
• Example: Artificial Anasazi
Brief Descriptions of Civil Servant
Exams (科挙試験) in China
• Establish and Keep the Bureaucracy to Support the Emperor of
Chinese Dynasties
• Origin：Han(漢)era（3c），Start: Sui（隋）era (6c), Continue: Tang(
唐), Establish:Song(宋)(10c), Thrive:Yuan(元)、Ming (明)、
end:Ching（清）(20c)
• The Longest History: over 1,400 years continued
• Applicants: over 300k persons/yr; #Passed: 300 persons/3yrs
(in Ching era)
• 3 or 4 levels Exams (Regional to Central)
• Levels of Candidates: sheng-yuan, kun-sheng; chien-sheng; chujen; kung-shih; chin-chi(進士) (6 levels)
• Exam Questions: Liberal Arts (Not Natural Sciences)
• 2-3 days exams!
• They did not make educational systems but only exam. systems
Brief Literature Review in Family Systems
• Roles of women in Cultural Capital Transfer
– “A wise daughter will make a wise wife and mother”(Mann).
• The Marriage System in China
– Since the sixteenth century, the upper class families in Hunan
area in China focused on the levels of women’s cultural and
literary talents are critical factors for successful marriage.
(Ko)
• History of Civil Service Examination
– It is an examination for recruitment of government officials,
which has been run for about 1,300 years.
The effect of relatives
 Elman(1991)
– It was possible for ordinary candidates to achieve academic
success, because they had bureaucrats among their relatives.
– To create elite families ensured success of the examinations.
– It guaranteed that such the background gained successful future
and political career.
– The candidates came from a family which had the tradition of
learning classics and the official language.
– Certain family lines could produce more successful candidates.
Successful Family Y
• The Y family in Changzhou, Jiangsu are is a typical case
• Y produced twenty-two successful candidates for the period of
more than twelve generations.
• There are genealogical records (Zupu)of 1,237 members
between 1468 and 1944 (China and Japan).
• Zupu is a paternal (fathers’) record including name, birth year,
year of death, achievement in life, wife’s name, number of
children, place of residence and other information for each
family member, which consists of mainly two parts:
– “Shixi" : general family tree.
– “Shibiao“: the details of the profile of each member.
• Each example is shown in the next figures.
Family Network
Unsuccessful
Cluster
Successful
Cluster
Shixi of the Y family
The Y family’s profile (“Shibiao”)
Research Questions:
• Why Successful and Un-Successfuls
• How were they Educated
• How they Transmit the Knowledge and
Roles of Family Systems
– Norms, Marriage Systems, (In)tangibles,…
• The Questions are hard to Answer only with
Literature Survey Studies
• ABM!
Zupu Pre-Processing
– The adjacency matrix which is changed from the “shixi”: the family tree.
– The attribute matrix which is changed from the “shibiao”: the family
profile.
Shixi: The Adjacency Matrix
Shibiao: The Attribution Matrix
Outline of the Agent Simulation
• Scenarios
– Each agent can transmit cultural capital,
from parent to child, from great-grandfather to great
grandson, from grandfather to grandson, or from uncle
and aunt to nephew.
– There are two categories of cultural capital.
• knowledge and art
– Children have two cultural characteristics by birth.
• knowledge and art
– A child's cultural capital depends on the synthetic effect s of his
characteristics and transmitted cultural capitals.
– Only knowledge cultural capital affects success in the examinations.
• Art cultural capital does not directly affect the rate of success.
• Parameters:
– Who is the transmitter (great-grandfather,
grandfather, father, mother, uncle, aunt).
– Degree of effect on individual cultural capital (rate
of cultural transmission from father and others)
– Education effect by child’s cultural characteristics.
– Degree of effect of the mother’s family home
(transmission rate of cultural capital).
– Degree of effect of the aunt’s married family
(transmission rate of cultural capital).
Relation among K &A C.P.
Cultural capital transmission function
clkc  m0  ( pskc  ra  psac )  i 1 (mi  clki  ra  clai )
6
clac  m0  ( psac  rk  pskc )  i 1 (mi  clai  rk  clki )
6
cl kc : knowledge cultural capital of a child
cl ac : art cultural capital of a child
ps kc : knowledge characteri stic of a child
ps ac : art characteri stic of a child
cl ki : knowledge cultural capital of member i
cl ai : art cultural capital of member i
ra : crossover rate from art cultural capital to knowledge cultural capital
rk : crossover rate from knowledge cultural capital to art cultural capital
mi : cultural capital transmiss ion rate of education and family members to child
Inverse Simulation
Forward Simulation
Inverse Simulation Method
Design the Model
Design a Model with Many Params.
Set Various Parameters
Set a Global Objective Fnc.
Execute Simulation
Execute Simulation to Optimize it
Evaluate Results
Evaluate Initial Parameters
They consider the approach Very Difficult!!
GA techniques work well!!
Evolving Societies by GA:
Inverse
Simulation
• Avoid manual parameter tuning
•
•
Evolve ‘good’ societies based on fitness functions associated with Socio-Metrics
Analyze the characteristics of the agents in the Evolved Society
Pre-determined Features
Acquired Features
n-interval
Micro-Level
Phenomena
Micro-Level
Behavior
n-interval
Genes of Society
Simulation of Artificial Societies
Fitness=Macro-Level Socio-metrics
Evaluation
Selection
Crossover
Mutation
Assumptions for IS
• Micro-Level Rich Functionality of the Agent Simulator
with Enough Number of Parameters
• Macro-Level Clear Specification of the Desired Results
like min f(…)
• Fast Execution of the Simulation
• Good GA-Based Techniques
History Simulator with IS
Rules, Parameters
If A then X
If B then Y
If C then Z
P1=0.3
P2=0.7
Family Tree
Agent
simulator
Simulated
attribution
matrix
0
F
1
M
0
F
M
F
F
MAS
0
M
0
0
Real
attribution
matrix
1
0
1
0
0
0
0
1
0
0
1
0
1
0
0
1
0
0
1
0
1
0
0
1
0
0
1
0
0
1
0
1
0
0
0
0
1
0
1
0
0
1
1
0
0
1
0
1
0
0
0
1
0
0
0
1
Evaluation
GA
If A then X
If B then Y
If C then Z
P1=0.3
P2=0.7
0
F
F
M
1
M
F
F
M
MAS
0
0
0
0
1
0
1
0
0
0
0
1
0
0
1
0
1
0
0
1
0
0
1
0
1
0
0
1
0
0
0
1
Evaluation
Experiments without Grid
Obtained Strategies:
transmit : clic  0.3 transmiti (cl p )  0.85 transmiti (cl gp )
transmit k : clkc  r (clkp  pskc )  (1  r )(clap  psac ),
transmit a : clac  r (clap  psac )  (1  r )(clkp  pskc )
if (maternal grandfather is a successful candidate) then
a child gets his cultural capital
else a child doesn’t get it
Effect by education = 0.4
Effect by cultural capital = 0.4
Crossover rate of cultural capital = 0.2
Who Educated Children?
Culture Transmitter to Children: Grand Father
Generation Effects:
Parents
F
M
F
M
F
Father : Granpa=1.0 : 2.8
Parents & Granpa
F
M
F
M
F
M
F
F
M
Granpa
F
M
F
M
F
F
M
What Let Children Learn?
Both Knowledge & Cultural Capitals from Parents(type5)
K Capitals of Child = r*[KC of Parents]*[KA of Child]
+ (1-r)*[AC of Parents]*[CA of Child]
A Capitals of 子Child = r*[AC of Parents]*[CA of Child]
+ (1-r)*[KC of Parents]*[KA of Child]
Cultural Crossover Rate:
Granpa, Parent
K. Directed
Child
K
0.2
A
K
A
0.8 0.2
0.2 0.8
K
A
Balanced
1.0
K
1.0
A
Who made them successful, again?
Women’s Roles
if (Mothers’ Father Succeeded) then
otherwise,
1.0
0.0
Education form Father to Daughter
F
F
M
M
Marriage
F
M
F
F
M
Education
From Mother
To Child
F
Support from
Wife Giver
Desirable Three types of ABS
Forward Simulation
Inverse Simulation
Design a Model
Design a Model
Set Various Parameters
Generate Parameters based on
Optimal Algorithm
Execute Simulation
Execute Simulation
Evaluate Results
Evaluate the Parameters
Repeat
Optimize
Model Selection
Design a Model
Generate a Subset of Parameters
based on Optimal Algorithm
Execute Inverse Simulation
based on this Subset of Parameters
Evaluate the Subset of Parameters
Optimize
Forward Simulation Architecture
Forward Simulation Master
Parameters
Property File
…
Trail -1
Trail -2
Individual
Queue
: Parameter Set
MAS
Get
…
…
Result -N
Return Put
…
P1=0.1
P2=0.3
P3=0.5
Simulated
Data
Evaluation
Notify
Trail -N
Results
Result -1
Result -2
Worker_1
Task Generation
Method
Simulation
Manager
Agent
simulator
Worker_N
Worker
Agent
P1=0.1
P2=0.3
P3=0.5
MAS
Inverse Simulation Architecture [Yang et al. 2009]
Inverse Simulation Master
Population
UNDX + MGG
…
Individual
Queue
: Parameter Set
Worker
Agent
Agent
Simulated
simulator Data
MAS
Evaluation
…
Call Evaluation
Method
Parallel
Return Evaluator
Notify
Survival
Put
Selection
Get
…
Making Kids
Rules,
Parameters
Worker_1
If A then X
If B then Y
P1=0.3
P2=0.7
Worker_N
If A then X
If B then Y
P1=0.3
P2=0.7
MAS
Model Selection Architecture
Ref. Figure 3
Model Selection Master
Population(Parameter Subset)
UNDX + MGG
…
Individual
Queue
: Subset of Parameters
Worker
Agent
Worker
…
Call Evaluation
Method
Parallel
Return Evaluator
Notify
Survival
Put
Selection
Get
…
Making Kids
Inverse
Master
Inverse
Master
Worker
Real-coded GA(UNDX+MGG) [Ono]
Real-coded GA to search for appropriate parameters in the
simulation.
Computationally Intensive! GOGA framework for parallel
computation.
GOGA Framework
Objective Function of H. ABS
n
m
min : Fitness   (cij  scij ) 2
i 1 j 1
n : the number of agent
m : the number of cultural capital
cij : The real cultural capital
sc ij : The exprimenta l observed cultural capital
Experimental Setups and Results
 Configurations :
• selection by tournament
• crossovers of MGG:
200
• alpha of UNDX:
0. 5
• beta of UNDX:
0.35
• number of societies:
50
• number of generations:
2000.
Parameters
People who transmit cultural
capital to child
Education Effect by the
characteristic of child
Effect by mother
Effect by aunt
Results
father, uncle, mother, aunt
3%
28%,if maternal grandfather is
a successful candidate.
6%, if father in aunt’s married
family is a successful candidate.
Crossover rate from art 100%
cultural capital to knowledge
cultural capital
Crossover
rate
from 0
knowledge cultural capital to
art cultural capital
Transmission method of Both cultural capitals of
cultural capital
knowledge
and
art
are
transmitted to the child from
parents.
Cultural Capital Transmission Functions
cl  m0  ( ps  ra  ps )  i 1 (mi  clki  ra  clai )
c
k
c
k
c
a
6
cl  m0  ps  i 1 mi  clai
c
a
c
a
6
cl ij : i' s cultural capital about j.
i : c  child,
p  parent.
j : k  knowledge cultural capital,
a  art cultural capital.
ra : crossover rate from art cultural capital to knowledge cultural capital
mi : cultural capital transmiss ionrate of education and family members to child
There is a strong bond in
the exchanges between artists and intellectuals, and
the relationships between brothers and sisters
Model Comparison
Forward Simulation
Inverse Simulation
合格者
知識資本シミュレーション
順シミュレーション結果
6
MSE=6.23
MSE=1.12
合格者
知識資本シミュレーション
8
5
4
合格者数・文化資本
合格者・文化資本
6
3
2
4
2
1
0
1450
1500
1550
1600
コーホート
1650
1700
0
1450
1750
Self Regression Model
1550
1600
コーホート
1650
1700
1750
Generalized Linear Model
MSE=4.75
合格者
知識資本（自己回帰モデル）
1500
合格者
知識資本（一般化線形モデル）
8
MSE=1.92
8
6
合格者数・知識資本
合格者数・知識資本
6
4
2
0
1460
1510
1560
1610
-2
コーホート
1660
4
2
1710
0
1460
1510
1560
1610
コーホート
1660
1710
Roles of Male Members
Father and uncle play most important roles in the family for
transmitting cultural capital to a child, and the influence of
father is a little stronger than that of the uncle.
Great-grandfather has little influence on his great-grandson,
which indicates that generation distance over three transmits
little cultural capital to a child.
The important role of a grandfather to his grandson is
replaced by the uncle‘s role ,which is because China has a
big family system and all the family members live together,
then uncle inherits the cultural capitals from grandfather and
transmit them to the child indirectly.
Roles of Female Members
The roles of mothers and aunts in a successful cluster are
influential.
Influential effects of aunt are discovered [Ko] from case
study:
 Which coincides with the Ko’s case study:
 Families, which belong to the same class and keep the relationship of marriage
over generations, bring up their children each other.
 Elite families to supplement marriage alliances, or simply to enhance a son's
educational opportunities.
Influential effects by the aunts, which are relatively smaller
than the ones by the mothers, although they would keep
the norm of a reciprocal relationship between families.
Comparison: Winners & Losers
Father: the Most Important Cultural Transmitter
The Cultural Influence to the Child:
Birth family of Mother > Married Family of Aunt.
Transmission of Knowledge
The Strategy to Success for Exams
• Father has the same responsibility as mother to
educate children.
• It is significant that combination effects of father,
uncle, mother and aunt are to maintain a successful
family norm.
• Both mother in wife-taker and aunt in wife-giver
have positive influence to success.
• A child has more possibility to grow up to a
successful candidates when he has more chances to
appreciate art.
• Education system is helpful to children.
Concluding Remarks
We have proposed a new method of Agent-Based
Simulation (ABS) Model using a family tree to study
history and cultural anthropology
Using a Grid System, Forward-, Inverse-Simulation, &
Model Selection Mechanisms work well
We have analyzed successful candidates of Chinese
civil service examinations with the ABS, which is based
on the principle of cultural capitals [Bourdieu 1979]
 We demonstrated that the roles of members of a family,
especially artists are important to transfer the cultural
capitals.
Two Messages
High Performance Computing is Critical for
Cutting-Edges of both Social Science
Researches and Design & Implementation of
Social Architectures!
Agent-Based Modeling is a New Art, and
“a lie that helps us see reality”
Acknowledgements
・Contributors:
Prof. Setsuya Kurahashi(Tsukuba U.), Dr. Keiko Kurahashi(Rikkyo U.),
Prof. Isao Ono, Ms. Chao Yang, and Mr. Toru Takahashi (Titech)
・References
[1] Setsuya Kurahashi, Takao Terano: Historical Simulation: A Study of
Civil Service Examinations, The Family Line and Cultural Capital in
China. Advances in Complex Systems (ACS) ,Vol.11, No. 2, pp. 187198 (April 2008)
[2] Chao Yang, Setsuya Kurahashi, Keiko Kurahashi, Isao Ono and Takao
Terano: Agent-Based Simulation on Women's Role in a Family Line on
Civil Service Exami-nation in Chinese History. Journal of Artificial
Societies and Social Simulation vol. 12, no. 2,2009
http://jasss.soc.surrey.ac.uk/12/2/5.html
[3] Chao Yang, Toru Takahashi, Bin Jiang, Isao Ono, Setsuya Kurahashi,
Takao Terano: A Grid-Oriented Social Simulation Framework for
Large Scale Agent-Based Modeling, Proc. 6-th Conference of
European Social Simulation Association (ESSA 2009), 2009.