Advances in Computational Social Science and Social Simulation
Francisco J. Miguel, Frédéric Amblard, Joan A. Barceló & Marco Madella (eds.)
Proceedings of the Social Simulation Conference 2014
Barcelona, Catalunya (Spain), September 15
Francisco J. Miguel
Autònoma University of Barcelona, Department of Sociology Laboratory for SocioHistorical Dynamics Simulation – LSDS Bellaterra Campus, UAB, 08193 Cerdanyola, Catalonia (Spain) EMail: miguel.quesada@uab.cat
Frédéric Amblard
IRIT Université Toulouse 1 Capitole
2, rue du Doyen Gabriel Marty, 31042 Toulouse (France) EMail: frederic.amblard@utcapitole.fr
Joan A. Barceló
Autònoma University of Barcelona, Department of Prehistory Laboratory for SocioHistorical Dynamics Simulation – LSDS Bellaterra Campus, UAB, 08193 Cerdanyola, Catalonia (Spain) EMail: juanantonio.barcelo@uab.es
Marco Madella
Pompeu Fabra University, Department of Humanities
Ramon Trias Fargas, 2527, 08005 Barcelona (Spain)
EMail: marco.madella@upf.edu
held at Barcelona, Catalunya (Spain), September 15, 2014
10th Artificial Economics Conference AE
10th Conference of the European Social Simulation Association ESSA 1
stSimulating the Past to Understand Human History SPUHH
Organized by
Laboratory for SocioHistorical Dynamics Simulation (LSDSUAB) Autònoma University of Barcelona, Bellaterra Campus, 08193 Cerdanyola, Spain
with suport from
European Social Simulation Association (ESSA), Autònoma University of Barcelona (UAB),
University School of Tourism and Hotel Management (EUTDHUAB), The SimulPast Project (INGENIO 2010),
Social Systems Engineering Center (INSISOC), Artificial Intelligence Research Institute (IIIACSIC),
Barcelona Supercomputing Center (BSC), Milà i Fontanals Institute (IMFCSIC),
Computer Applications & Quantitative Methods in Archaeology (CAA).
T
This work is licensed under a
Creative Commons AttributionNonCommercialNoDerivatives 4.0 International License
<http://creativecommons.org/licenses/byncnd/4.0/>
Typesetting: Cameraready by author, using IEEEtranbased templates (tex, odt, doc) Version 3, April 2015
(cc) 2015 CC BYNCND 4.0
both the “10th AE Series Conference”, the “10 European Social Simulation Association Annual Meeting”, and the “SPUHH Conference”. Readers will find results of recent research on computational social science and social simulation economics, management, sociology, history
written by leading experts in the field. SOCIAL SIMULATION (former ESSA) conferences
constitute annual events which serve as an international platform for the exchange of ideas and
discussion of cuttingedge research in the field of social simulations, both from the theoretical as
well as applied perspective, and the 2014 edition benefits from the crossfertilization of three
different research communities into one single event. The volume consists of 121 papers,
corresponding to most of the contributions to the joint conferences, in three different formats: short
abstracts (presentation of workinprogress research), posters (presentation of models and results),
and full papers (presentation of social simulation research including results and discussion). This
compilation is completed with indexing lists to help finding articles by title, author and thematic
content. We are convinced that this book will serve interested readers as a useful compendium
which presents in a nutshell the most recent advances at the frontiers of computational social
sciences and social simulation research.
On behalf of the 2014 Social Simulation Conference organizing committee, we would like to extend you a very warm welcome to the SSC 2014 meeting at the Autònoma University of Barcelona (UAB). The Bellaterra Campus has a long history of involvement with social simulation, organizing previous meetings and pioneering teaching and research of computer simulation for the study of social, economic and historical phenomena, and so it is a privilege to welcome researchers from such a variety of fields.
This year we host three different, but closely related, communities and this week promise to be a stimulating combination of symposia, discussion sessions and plenary talks from speakers across the wide spectrum of Artificial Economics, Artificial Intelligence, Computational Sociology, Historical Simulation and other Computational Modelling approaches to social phenomena. In addition to the plenary talks of our guests keynote speakers, the conference are intended to foster dialogue and debate – we hope you'll find old and new topics thought provoking.
We look forward to meeting you at the daily coffee breaks and luncheons, at the Catalonian Wine Tasting reception on Monday afternoon, and at the Conference Dinner in Barcelona's Old Harbour on Wednesday evening. We would like to thank both the ESSA management committee, the AE series meetings committee, and the organizers of SPUHH for selecting our Campus to host SSC'14.
And we like to thank all the Tutors for their commitment in the “Tools Tutorial Day” on Monday, the organizers of the modelling workshop ESSA@work, all the reviewers of the submitted
contributions, the staff of the Laboratory for SocioHistorical Dynamics Simulation (LSDSUAB) and the rest of the the local organizing committee, including the student helpers for all their hard work in making the event a success.
Francesc J. Miguel, Conference Chair Frederic Amblard, AE Chair
Joan A. Barceló and Marco Madella, SPUHH CoChairs
The AE 10th contributions will be published in a special Springer volume:
Amblard, F., Miguel, F.J., Blanchet, A., Gaudou, B. (Eds.) Advances in Artificial Economics, Series: Lecture Notes in Economics and Mathematical Systems, Vol. 676.
SpringerVerlag. ISBN 9783319095776
(Contents, Thematic, Authors)
Modelling Routeways in a Landscape of Esker and Bog (O'Brien) 20 Roman Bazaar or Market Economy? An Agentbased Network Model of Tableware Trade and Distribution in
the Roman East (BrughmansPoblome) 29
Calm Before the Storm? Modelling Military Supply and Movement (MurgatroydGaffney) 33
Personal Protective Behaviour During an Epidemic (BadhamGilbert) 38
Strategic Interactions and Information Exchange on Networks: An Agent Based Simulation Model of Landowner Behaviour in Conservation Incentive Schemes (BanerjeeMaharaj) 42 Humanintheloop simulation based system for more effective allocation and training of experimenters' groups in stimulation of biotechnological processes (MetzgerSkupin) 47
A Platform for Analyzing Accessfriendly Transportations for Elderly People Using GIS on Agentbased Model (DaitoTanida) 51
Cultural and genetic transmission in the JomonYayoi transition examined in agentbased demographic simulation (MatsumotoSasakura) 57
Moderate and Polarized Opinions: Using Empirical Data for an AgentBased Simulation (StefanelliSeidl) 61 Simulating the influence of sociospatial structures on energyefficient renovations (FriegeChappin) 65
Recent progress on formal and computational model for A.Smiths Invisible Hand paradigm (SzubaetAL) 76 Innovation, Demand, and Finance in an Agent BasedStock Flow Consistent model (CaianietAL) 88
An empirical economic model to reveal behaviour characteristics driving the evolution of agriculture in Belgium (MaesPassel) 92
Agedependent Mortality, Fecundity, Mobility Effects on the Neolithic Transition (PerezLosada) 105
Social Scientists, Qualitative Data, and AgentBased Modeling (Seidl) 110
Social Contagion and Homophily within Romantic Network (Linares) 114
Triadic Balance and Closure as Drivers of the Evolution of Cooperation (RighiTakacs) 121
Rise, Fall and Abandonment in the Zambezi Plateau: An AgentBased Model using the Canonical Theory (Bogle) 125 The Linkage between Financial Market and Real Economy:The Analysis with An Agent Based simulation (SuzukietAL) 131
The Individual Agent Makes a Difference in Segregation Simulation (Koch) 137
Beyond HypothesisTesting: using Approximate Bayesian Computation for comparing multiple models of cultural transmission in Neolithic Europe (Crema) 147 Communication apprehension, selfesteem and the Leviathan model (HuetShtiliyanova) 150 Simulating Extortees: Group Structures and Reasoning Modes (Elsenbroich) 161 Rewinding the Dynamics between two Japanese Ancient Descents: What would happen from the Jomon to the Yayoi Periods in Japan (SakahiraTarano) 163
Population spread and cultural transmission in Neolithic transitions (FortetAL) 175
Modelling EnergyConsuming Social Practices as Agents (BalkeetAL) 179
A spatially explicit agentbased model of opinion and reputation dynamics (VanVoornetAL) 183 DITCH: A Model of Interethnic Partnership Formation (MeyeretAL) 187
An agentbased Model to Study Customers’ Engagement with Brands from a ServiceDominant Logic Perspective (RajapakseTerano) 191
Simulating the Emergence of the Organizing Structures of Work (Backström) 203
Effective population and phenotypegenotype decoupling in cultural evolution (BortolinietAL) 210
Modeling Human Stability and Change in Organizations (KahlMeyer) 213
Bounded Confidence, Radical Groups, and Charismatic Leaders (Hegselmann) 217
building evidence for the Water Supply of Constantinople (SnyderDilaver) 224 Simulating social influence dynamics from observational data: the case of secessionist flags in Barcelona’s
balconies (NogueraetAL) 226
Knowledge transfer dynamics: how to model knowledge in the first place? (Guechtouli) 229 Social Simulation of Commercial and Financial Behaviour for Fraud Detection Research (LopezRojas
Axelsson) 243
Use of an agentbased model to explore urban transitions in commuter cycling (AbbasetAL) 253 An AgentBased Simulation of the Emergence of Partnership Systems in Early Renaissance Florence (Comer
Comer) 258
Modelling Interactions and Feedback Mechanisms in Land Use Systems (ChenetAL) 262 MultiScale AgentBased Simulation of LongTerm Dispersal Processes: Challenges in Modeling Hominin
Biogeography and Expansion (TimmetAL) 266
Organizational Routines: An Agent Based Model Replication (Hauke) 269
Modeling Population Dynamics of Online Communities (BaggioetAL) 272
Populating Virtual Cities with Diverse Physiology Driven Crowds of Intelligent Agents (TrescaketAL) 275 The Effect of Spatial Clustering on Stone Raw Material Procurement (OestmoetAL) 287 The Effect of Landscape Patterns on Foraging Strategies of HunterGatherers: An Empirical AgentBased
Modeling Approach (JanssenHill) 290
Models of Information Spread in Structured Populations (Voorhees) 293
From evidence to criminal agents (NeumannLotzmann) 301
Mafia war: simulating conflict resolution in criminal organizations (NeumannLotzmann) 304
The CEDSS Model of Direct Domestic Energy Demand (GottsPolhill) 307
Informing agent based models with discrete choice analysis: diffusion of solar PV in the Netherlands (Araghi
etAL) 318
The Internet As a Catalyst for Social Movements: A Simulation of Social Media Mechanisms in the Context
of the Arab Spring and Occupy Movements (Wiersma) 322
Information Technology and the Topologies of Transmission: a Research Area for Historical Simulation
(Gotts) 325
Rise and decline process of online communities: Modeling social balance of participants (AsatanietAL) 329 Testing the resilience of agropastoralists communities in arid margins through ABM (LancelottietAL) 339 Tackling Model Selection and Validation: an Information Theoretic Criterion (Lamperti) 342 Simulating land use of prehistoric wetland settlements: did excessive resource use necessitate a highly
dynamic settlement system? (Baum) 351
An Agentbased Concept to Analyze EliteAthletes’ Doping Behavior (WestmattelmannetAL) 355 How passenger decides a checkin option in an airport: SelfService Technology Adoption model in
passenger process (UedaKurahashi) 366
Party Competition and Voter DecisionMaking (Reinermann) 377
Reconstructing the Question of School Choice: Towards a Geographical AgentBased Model for Chile
(BlancoetAL) 381
Teaching Simulation on Collaborative Learning, Ability Groups and Mixedability Groups (Kurahashi
Kuiyoshi) 400
A Markov Chain approach to ABM calibration (Fabretti) 404
Quality, advertisement and social influences in cultural market: The case of motion picture (DelreetAL) 408 Sensitivity analysis for agentbased models: a low complexity testcase (tenBroekeetAL) 422 The quality of social simulation: an example from research policy modelling (AhrweilerGilbert) 426 Modelling cultural shift: Application to language decline and extinction (IsernFort) 440
Simulating pedestrians through the innercity: an agentbased approach (RoseetAL) 463 Computational Environment Behavior Research: Case Studies of Sustainability and Population Collapse in a
Northern Arizona Region (Voss) 467
Diffusion of ideas, social reinforcement and percolation (TuretAL) 470
Economic Sustainability in Relation to Demographic Decline of Celtic Agglomerations in Central Europe:
MultipleScenario Approach (OlsevicovaDanielisova) 481
How real estate agents behavior affects urban growth: an agentbased model approach (CantergianietAL) 491 Agent Activation in a Replication of the ZeroIntelligence Trader Double Auction Market Simulation
(ComeretAL) 494
Partner selection supports reputationbased cooperation in a Public Goods Game (ViloneetAL) 504 An agentbased model of firm location with different regional policies (PabloMartietAL) 512 More for Less: on Consumer Rationality and Bargaining Power on Telecommunication Markets (Olczak
Kaminski) 518
Demographic agentbased simulation of Gambians immigrants in Spain (MontañolaSalesetAL) 531 Analysing a Complex AgentBased Model Using DataMining Techniques (EdmondsetAL) 535 Job Satisfaction as a Unified Mechanism for Agent Behaviour on a Labour Market with Referral Hiring
(Tarvid) 547
The PLS Agent – Agent Behavior Validation by Partial Least Squares (LorscheidetAL) 555 Qualitative spatial representation in agentbased models (PolhilletAL) 563 Technology development and political and economic power: evolution of global inequality (Inoue
ChaseDunn) 569
Strategic decision support for marketing communication: an agentbased simulation of consumer attitudes to
smart home appliances (vanDametAL) 573
The urbanization process in Central Italy: A network approach (FulminanteetAL) 577
An AgentBased Model of Consensus Building (ScholzetAL) 579
The evolution of cooperative versus noncooperative governance of smallscale fisheries (SchluteretAL) 590 A theory driven, spatially explicit agentbased simulation to model the economic and social implications of
urban regeneration (Picascia) 594
Beyond Simulations: Serious Games for Training Interpersonal Skills in Law Enforcement (LinssenetAL) 604
Modelling cooperation in Bali irrigation (WijermansSchluter) 608
Modelling the impact of beliefs and communication on attitude dynamics: a cognitive agentbased approach
(BrousmicheetAL) 612
Towards metadata standards for sharing simulation outputs (PolhilletAL) 624 Computing Job Satisfaction with Social Comparison Process: an AgentBased Approach (ChapuisKant) 628
On Fragmentation and Scientific Progress (BaliettietAL) 636
Generic bottomup buildingenergy models for developing regional energy transition scenarios (KnoerietAL) 641 The Efficiency of Organizational Withdrawal vs Commitment (SibertinBlancTeran) 647
High Skilled Emigration and Wealth Distribution (MagessiAntunes) 656
Intellectual Property Framework and Dynamics of Technology Change under Sequential Innovation
(SenguptaSena) 663
A Few Bad Apples Are Enough: An AgentBased Peer Review Game (CabotaetAL) 665 TransMob: An Agent Based Simulation of Transport Demand and Residential Mobility in South East Sydney
(PerezetAL) 668
Comparing Two Models of Cultural Standardization Emergence in Hunter Gatherer and Sedentary Societies
(DelCastilloBarcelo) 675
Investigating Opinion Dynamics using the FreqNet model (BoermaAlbersJager) 678 Behavioural Responses to Epidemics: Report from a Virtual Experiment (MaharajetAL) 680 Towards Modeling a MultiAgent System for Balkan Neolithic Spread (ZanottietAL) 681
City of Uruk 3000 B.C.: Using genetic algorithms, dynamic planning and crowd simulation to reenact
everyday life of ancient Sumerians (TrescaketAL) 689
Cooperation maintained by defect and collapsed by reward in a generalized metanorms game (Yamamoto
etAL) 693
Market dynamics in the Dutch Pork Sector (AmbrosiusetAL) 694
Agentbased modelling of agricultural water abstraction in response to climate change and policies: In East
Anglia, UK (SwinscoeetAL) 695
An agentbased model of a socialecological system: A case study of disease management in potato
cultivation (PacillyetAL) 698
On infrastructure network design with agentbased modelling (ChappinHeijnen) 700 Does follower of majority accelerate polarization or diversity of culture? (OgawaYamamoto) 702 Simulating Value CoCreation in B2B Financial Service: An Application of Empirical AgentBased Modeling
(MizunoetAL) 703
Robustness of cooperation to movement patterns in a HunterFisherGatherer model (PeredaetAL) 704 Exploring the dynamics of the world energy system: An agentbasedSystem dynamics model (Kooshknow
etAL) 707
Making city in the NonCity: the integration of irregular settlements in Andalusia: A case study (PiñeroetAL) 709
User Profiling in Multiplayer Serious Games (BouferaBendella) 711
ESSA SESSIONS
Spatial and EcologicalEconomic issues
Jonas Friege and Emile Chappin: “Simulating the influence of sociospatial structures on energyefficient
renovations” 65
Alessandro Caiani, Eugenio Caverzasi, Antoine Godin, Alberto Russo, Luca Riccetti and Mauro Gallegati:
“Innovation, Demand, and Finance in an Agent BasedStock Flow Consistent model” 88 Dries Maes and Steven Van Passel: “An empirical economic model to reveal behaviour characteristics driving
the evolution of agriculture in Belgium” 92
Yoshito Suzuki and Akira Namatame: “The Linkage between Financial Market and Real Economy: The
Analysis with An Agent Based simulation” 131
Tina Balke, Thomas Roberts, Maria Xenitidou and Nigel Gilbert: “Modelling EnergyConsuming Social
Practices as Agents” 179
George Van Voorn, Arend Ligtenberg and Guus ten Broeke: “A spatially explicit agentbased model of
opinion and reputation dynamics” 183
Edgar Alonso LopezRojas and Stefan Axelsson: “Social Simulation of Commercial and Financial Behaviour
for Fraud Detection Research” 243
Yang Chen, Arend Ligtenberg, Martha Bakker and Arnold Bregt: “Modelling Interactions and Feedback
Mechanisms in Land Use Systems” 262
Nicholas Gotts and Gary Polhill: “The CEDSS Model of Direct Domestic Energy Demand” 307 Yashar Araghi, Esther Park Lee and L. Andrew Bollinger: “Combining discrete choice with agent based
models: diffusion of solar PV in the Netherlands” 318
Christian Blanco, Nelson Paulus, Catalina Canals, Felipe Fábrega, Cristián Aguirre and Camila Mena:
“Reconstructing the Question Of School Choice: Towards A Geografical AgentBased Model For Chile” 381 Jane Rose, Arend Ligtenberg and Stefan van der Spek: “Simulating pedestrians through the innercity: an
agentbased approach” 463
Kenneth Comer, Andrew Loerch and Robert Axtell: “Agent Activation in a Replication of the Zero
Intelligence Trader Double Auction Market Simulation” 494
Federico PabloMarti, Carlos Muñoz and Juan Luis Santos: “Measuring spatial outcomes in an agentbased
model of several regions with different policies” 512
Maja Schlüter, Emilie Lindkvist and Xavier Basurto: “The evolution of cooperative versus noncooperative
governance of smallscale fisheries” 590
Stefano Picascia: “A theory driven, spatially explicit agentbased simulation to model the economic and social
implications of urban regeneration” 594
Nanda Wijermans and Maja Schlüter: “Modelling cooperation in Bali irrigation” 608 Christof Knoeri, Alessandra Goetz and Claudia R. Binder: “Generic bottomup buildingenergy models for
developing regional energy transition scenarios” 641
Simulation of Economic Processes
Masatora Daito and Noriyuki Tanida: “A study on Optimized Combination of Accessfriendly Transportations
for Elderly People Using Agentbased Model” 51
Tadeusz Szuba, Stanislaw Szydlo and Pawel Skrzynski: “Recent progress on formal and computational model
for A. Smiths Invisible Hand paradigm” 76
Chathura Rajapakse and Takao Terano: “An agentbased Model to Study Customers’ Engagement with Brands
from a ServiceDominant Logic Perspective” 191
Francesco Lamperti: “Tackling Model Selection and Validation: an Information Theoretic Criterion” 342 Daniel Westmattelmann, Marcel Goelden, Gerhard Schewe and Sascha Hokamp: “An Agentbased Concept to
Analyze EliteAthlete’s Doping Behavior” 355
Keiichi Ueda and Setsuya Kurahashi: “How passenger decides a checkin option in an airport: SelfService
Technology Adoption model in passenger process” 366
Annalisa Fabretti: “A Markov Chain approach to ABM calibration” 404
Sebastiano Delre, Wander Jager and Marco Janssen: “Quality, advertisement and social influences in cultural
market: The case of motion picture” 408
Tomasz Olczak and Bogumił Kamiński: “More for Less: on Consumer Rationality and Bargaining Power on
Telecommunication Markets” 518
Alexander Tarvid: “Job Satisfaction as a Unified Mechanism for Agent Behaviour on a Labour Market with
Referral Hiring” 547
Koen van Dam, Maarten van der Sanden and Jeroen Stragier: “Strategic decision support for marketing
communication: an agent based simulation of consumer attitudes to smart home appliances” 573 Christophe SibertinBlanc and Oswaldo Teran: “The Efficiency of Organizational Withdrawal vs
Commitment” 647
Nuno Magessi and Luis Antunes: “Emigration and Wealth Distribution” 656
Abhijit Sengupta and Vania Sena: “Intellectual Property Framework and Dynamics of Technology Change
under Sequential Innovation” 663
Cognitive Models
Jennifer Badham and Nigel Gilbert: “Personal Protective Behaviour During an Epidemic” 38 Simanti Banerjee and Savi Maharaj: “Strategic Interactions and Information Exchange on Networks: An Agent
Based Simulation Model of Landowner Behaviour in Conversation Incentive Schemes” 42 Corinna Elsenbroich: “Simulating Extortees: Group Structures and Reasoning Modes” 161 Cara Kahl and Matthias Meyer: “Modeling Human Stability and Change in Organizations” 213 Jonas Hauke: “Organizational Routines An Agent Based Model Replication” 269
Holger Reinermann: “Party Competition and Voter DecisionMaking” 377
Carolina C. Cantergiani, Joana Barros and Montserrat Gómez Delgado: “How Real Estate Agents Behavior
Affects Urban Growth: An ABM Approach” 491
Geeske Scholz, Claudia PahlWostl and Art Dewulf: “An AgentBased Model of Consensus Building” 579 KeiLeo Brousmiche, JeanDaniel Kant, Nicolas Sabouret, Stephane Fournier and Francois PrenotGuinard:
“Modeling the impact of beliefs and communication on attitude dynamics: a cognitive agentbased approach” 612 Kevin Chapuis and JeanDaniel Kant: “Computing Job Satisfaction from social comparisons: an agentbased
approach” 628
Social Conflict and Social Simulation
Simone Righi and Karoly Takacs: “Triadic Balance and Closure as Drivers of the Evolution of Cooperation” 121 Jacopo Baggio, Miles Manning, Lingfei Wu and Marco Janssen: “Modeling population dynamics of online
communities” 272
Martin Neumann and Ulf Lotzmann: “Mafia war: A simulation model of conflict resolution in criminal
Modeling social balance of participants” 329 Luis Gustavo Nardin, Giulia Andrighetto, Rosaria Conte and Mario Paolucci: “From Anarchy to Monopoly:
How Competition and Protection Shaped Mafia's Behavior” 444
Using Qualitative Data
Annalisa Stefanelli and Roman Seidl: “Moderate and Polarized Opinions. Using Empirical Data for an Agent
Based Simulation” 61
Roman Seidl: “Social Scientists, Qualitative Data, and AgentBased Modeling” 110 Jose Antonio Noguera, Antonio Parravano, Paula Hermida and Jordi TenaSanchez: “Simulating Social
Influence Dynamics From Observational Data: The Case Of Secessionist Flags in Barcelona's Balconies” 226 Syed Muhammad Ali Abbas, Rachel Aldred, Zaid Chalabi and James Woodcock: “Use of an agentbased
model to explore urban transitions in commuter cycling” 253
Martin Neumann and Ulf Lotzmann: “From evidence to criminal agents: Modelling the collapse of a criminal
network” 301
Gary Polhill, Nick Gotts, Amparo AlonsoBetanzos, Noelia SanchezMaroño, Oscar FontenlaRomero, Tony
Craig and Ricardo GarciaMira: “Qualitative spatial representation in agentbased models” 563 Mieczyslaw Metzger and Piotr Skupin: “Humanintheloop simulation based system for more effective
allocation and training of experimenters' groups in stimulation of biotechnological processes” 47
Synthetic Populations
Ruth Meyer, Huw Vasey and Laurence LessardPhillips: “DITCH: A model of interethnic partnership
formation” 187
Tomas Trescak, Anton Bogdanovych and Simeon Simoff: “Populating Virtual Cities with Diverse Physiology
Driven Crowds of Intelligent Agents” 275
Cristina MontañolaSales, Josep CasanovasGarcia, Jose Maria CelaEspín and Adriana KaplanMarcusán:
“Demographic agentbased simulation of Gambians immigrants in Spain” 531
Claire Little and Bruce Edmonds: “Analysing a Complex Model of Social Influence over a Dynamic
Demographic Population” 535
Pascal Perez, Nam Huynh, Vu Lam Cao, Rohan Wickramasuriya, Matthew Berryman: “TransMob: An Agent
Based Simulation of Transport Demand and Residential Mobility in South East Sydney” 668
Methodologic issues
Guus ten Broeke, George Van Voorn and Arend Ligtenberg: “Sensitivity analysis for agentbased models: a
low complexity testcase” 422
Petra Ahrweiler and Nigel Gilbert: “The quality of social simulation: an example from research policy
modelling” 426
Iris Lorscheid, Matthias Meyer, Sandra Pakur and Christian Ringle: “The PLS Agent – Agent Behavior
Validation by Partial Least Squares” 555
Gary Polhill, Terry Dawson, Dawn Parker, Xiongbing Jin, Kirsten Robinson, Tatiana Filatova, Alexey Voinov, Michael Barton, Edoardo Pignotti and Peter Edwards: “Towards metadata standards for sharing
simulation outputs” 624
Sylvie Huet and Anastasia Shtiliyanova: “Communication apprenension, selfesteem and the Leviathan
model” 150
Rainer Hegselmann: “Bounded Confidence, Radical Groups, and Charismatic Leaders” 217 Javier AlvarezGalvez: “Network models of minority opinion spreading” 220 Widad Guechtouli: “Knowledge transfer dynamics: how to model knowledge in the first place?” 229 Elena M. Tur, Paolo Zeppini and Koen Frenken: “Percolation of ideas, social pressure and homophily” 470
Simulating the Social Processes of Science
Burton Voorhees: “Models of Information Spread in Structured Populations” 293 Stefano Balietti, Michael Maes and Dirk Helbing: “On Fragmentation and Scientific Progress” 636 Juan Batista Cabotà, Lorena Cadavid, Francisco Grimaldo, Giangiacomo Bravo and Flaminio Squazzoni: “A
Few Bad Apples Are Enough. An AgentBased Peer Review Game” 665
Evolution of Institutions
Andreas Koch: “The Individual Agent Makes a Difference in Segregation Simulation” 137 Amineh Ghorbani and Giangiacomo Bravo: “The Emergence of Institutions for the Management of the
Commons” 455
Daniele Vilone, Francesca Giardini and Mario Paolucci: “Partner selection supports reputationbased
cooperation in a Public Goods Game” 504
Social Simulation for Serious Games
Setsuya Kurahashi and Keisuke Kuniyoshi: “Teaching Simulation on Collaborative Learning, Ability Groups
and Mixedability Groups” 400
Jeroen Linssen, Thomas de Groot, Mariët Theune and Merijn Bruijnes: “Beyond Simulations: Serious Games
for Training Interpersonal Skills in Law Enforcement” 604
A
Cristián Aguirre...381
Petra Ahrweiler...426
Rachel Aldred...253
SyedMuhammad Ali Abbas...253
Edgar Alonso LopezRojas...243
Amparo AlonsoBetanzos...563
Javier AlvarezGalvez...220
Giulia Andrighetto...444
Luis Antunes...656
Yashar Araghi...318
Kimitaka Asatani...329
Stefan Axelsson...243
Robert Axtell...494
B Tomas Backström...203
Jennifer Badham...38
Jacopo Baggio...272
Martha Bakker...262
Stefano Balietti...636
Tina Balke...179
Simanti Banerjee...42
Joana Barros...491
Michael Barton...624
Xavier Basurto...590
Matthew Berryman...668
Claudia Binder...641
Christian Blanco...381
Anton Bogdanovych...275
L. Andrew Bollinger...318
Giangiacomo Bravo...455, 665 Arnold Bregt...262
KeiLeo Brousmiche...612
Merijn Bruijnes...604
C Carolina C. Cantergiani...491
JuanBatista Cabotà...665
Lorena Cadavid...665
Alessandro Caiani...88
Catalina Canals...381
Josep CasanovasGarcia...531
Eugenio Caverzasi...88
JoseMaria CelaEspín...531
Zaid Chalabi...253
Emile Chappin...65
Kevin Chapuis...628
Yang Chen...262
Kenneth Comer...494
Rosaria Conte...444
Tony Craig...563
D Masatora Daito...51
Terry Dawson...624
Thomas de Groot...604
Sebastiano Delre...408
Art Dewulf...579
Marianne Döös...203
E Bruce Edmonds...535
Peter Edwards...624
Corinna Elsenbroich...161
Annalisa Fabretti...404
Tatiana Filatova...624
Oscar FontenlaRomero...563
Stephane Fournier...612
Koen Frenken...470
Jonas Friege...65
G Mauro Gallegati...88
Ricardo GarciaMira...563
Amineh Ghorbani...455
Francesca Giardini...504
Nigel Gilbert...38, 179, 426 Antoine Godin...88
Marcel Goelden...355
Alessandra Goetz...641
Montserrat Gómez Delgado...491
Nick Gotts...307, 563 Francisco Grimaldo...665
Widad Guechtouli...229
H Jonas Hauke...269
James Hazy...203
Rainer Hegselmann...217
Dirk Helbing...636
Paula Hermida...226
Sascha Hokamp...355
Sylvie Huet...150
Nam Huynh...668
Marco Janssen...272, 408 Xiongbing Jin...624
Peter Johansson...203
K Cara Kahl...213
Bogumił Kamiński...518
JeanDaniel Kant...612, 628 Adriana KaplanMarcusán...531
Christof Knoeri...641
Keisuke Kuniyoshi...400
Setsuya Kurahashi...366, 400 L Vu Lam Cao...668
Francesco Lamperti...342
Laurence LessardPhillips...187
Arend Ligtenberg...183, 262, 422, 463 Francisco Linares...114
Emilie Lindkvist...590
Jeroen Linssen...604
Claire Little...535
Andrew Loerch...494
Iris Lorscheid...555
Ulf Lotzmann...301, 304 M Michael Maes...636
Dries Maes...92
Nuno Magessi...656
Andreas Koch...137
Chathura Rajapakse...191
Holger Reinermann...377
Luca Riccetti...88
Simone Righi...121
Christian Ringle...555
Thomas Roberts...179
Kirsten Robinson...624
Jane Rose...463
Alberto Russo...88
S Nicolas Sabouret...612
Noelia SanchezMaroño...563
JuanLuis Santos...512
Gerhard Schewe...355
Maja Schlüter...590, 608 Geeske Scholz...579
Roman Seidl...61, 110 Vania Sena...663
Abhijit Sengupta...663
Anastasia Shtiliyanova...150
Christophe SibertinBlanc...647
Simeon Simoff...275
Pawel Skrzynski...76
Piotr Skupin...47
Flaminio Squazzoni...665
Annalisa Stefanelli...61
Jeroen Stragier...573
Yoshito Suzuki...131
Tadeusz Szuba...76
Stanislaw Szydlo...76
T Karoly Takacs...121
Miles Manning...272
Camila Mena...381
Mieczyslaw Metzger...47
Ruth Meyer...187
Matthias Meyer...213, 555 Cristina MontañolaSales...531
Carlos Muñoz...512
N Akira Namatame...131
LuisGustavo Nardin...444
Martin Neumann...301, 304 JoseAntonio Noguera...226
O Hirotada Ohashi...329
Tomasz Olczak...518
P Federico PabloMarti...512
Claudia PahlWostl...579
Sandra Pakur...555
Mario Paolucci...444, 504 Esther Park Lee...318
Dawn Parker...624
Antonio Parravano...226
Nelson Paulus...381
Pascal Perez...668
Stefano Picascia...594
Edoardo Pignotti...624
Gary Polhill...307, 563, 624
Francois PrenotGuinard...612
Guus ten Broeke...183, 422
Jordi TenaSanchez...226
Oswaldo Teran...647
Takao Terano...191
Mariët Theune...604
Fujio Toriumi...329
Tomas Trescak...275
Elena M. Tur...470
U Keiichi Ueda...366
V Steven Van Passel...92
George Van Voorn...183
Stefan Van der Spek...463
Koen Van Dam...573
Maarten Van der Sanden...573
Daniele Vilone...504
Alexey Voinov...624
Burton Voorhees...293
W Daniel Westmattelmann...355
Rohan Wickramasuriya...668
Wybo Wiersma...322
Nanda Wijermans...608
James Woodcock...253
Lingfei Wu...272
X Maria Xenitidou...179
Z
Paolo Zeppini...470
Abstract—With the models used in this research, we can identify routeways which can be used to understand landscape and contextualise archaeological remains, while also learning about the decision-making process of people in the past and how they negotiated the landscape. ArcGIS and NetLogo are used to demonstrate the cumulative process which leads to the creation and evolution of routeways over time in a series of actions that approaches efficiency. The environment of North Offaly in the Irish Midlands is used as an example, as it is a landscape of natural routeways and obstacles for which we have rich archaeological and documentary evidence supporting interpretation of movement.
I. INTRODUCTION
HE aim of this research is to understand how people exploited natural routeways and manoeuvred around obstacles in the landscape in the past, using the archaeolog- ical evidence from North Offaly in the Irish midlands to ex- plore this question. This research uses modelling and com- puter applications, augmented by fieldwork and documen- tary sources, to identify likely routeways.
T
Two digital approaches are used, namely Least Cost Paths to calculate a routeway, and Agent-Based Modelling to grow [1] one. ArcGIS 9.3 is used, in what is considered a routine method to identify potential routes through the ap- plication of Least Cost Paths. NetLogo 5.0.3 [2] has been used to emulate individual actions which lead to the evolu- tion of routeways. While Least Cost Path procedures are ideal for identifying the optimal path through a landscape, the process has access to global information, which is not what agents on the ground experience when attempting to negotiate the landscape. Modelling allows us to investigate the overall evolution of a routeway as individual agents have access only to local information, allowing them to ap- proach the optimal path over time through a process of iter- ative attempts to traverse a landscape.
The outputs may be used to point to parts of the land - scape that merit further research in the field, and compari - son of both results to the archaeological and documentary record can improve the parameters in both simulations and help to develop a method which can be used in other study areas for which we do not have such rich records.
This research is funded by the Galway Doctoral Research ScholarshipScheme of the College of Arts, Social Sciences and Celtic Studies, National University of Ireland, Galway
II. THE STUDY AREA
A. The Landscape of North Offaly
The landscape of North Offaly (Fig. 1) is dominated with esker, bog and, in the past, extensive natural woodland. An esker is a long, sinuous ridge of sand and gravel, which are the remains of deposits left by rivers of melt-water beneath the surface of glaciers 15,000 years ago. In Ireland, a series of these ridges stretches from the East Coast to the West Coast and are known by the collective name of the Eiscir Riada. Some of the finest examples of high-sided and sin- gle-crested eskers are found in the study area (see [3]). The bogs, which are slightly younger, began to form about 10,000 years ago as glacial retreat filled dips and valleys with nutrient-rich meltwater. Poor drainage caused these shallow lakes to build up with partially decomposed plant material and eventually they grew into the typical dome shape of raised peat bogs. The Irish midlands are renowned for their raised bogs, or the Bog of Allen as they are gener- ally known, and a number of archaeological surveys and ex- cavations have demonstrated their importance since early prehistoric times [4], [5], [6]. A stretch of dry land, known as the Midland Corridor [7], bisects this landscape in a northeast by southwest orientation, acting as a major inter- regional routeway and valuable agricultural land. When Ire- land was first populated around 7800BC, the eskers were in already in place and the bogs were in their infancy, so these features would have influenced human activities since the arrival of the first settlers in Ireland.
B. Eskers
The eskers, being well-drained, elevated, relatively straight and flanked by wetlands, are quite suitable for routeways, as is clear from the large number of trails and roads currently located on these ridges (see Rahugh Ridge, Fig. 8). The early medieval routeway known as the Slighe Mór, which is associated with the birth of King Conn Céad- cathach and therefore usually dated to the early 2nd century AD, is defined for much of its course by the Eiscir Riada.
From the
Modelling Routeways in a Landscape of Esker and Bog
Yolande O' Brien Department of Archaeology, National University of Ireland,
Galway.
Email: y.obrien2@nuigalway.ie
early medieval period on there is a considerable increase in the amount of settlement, particularly ecclesiastical settle- ment, along the course of the eskers. The presence of a small number of standing stones and burials in proximity to eskers suggest a significance to this feature in prehistory also, but at this time the Midland Corridor with its north- east-southwest axis would have been the more important route. The esker must nevertheless, have been an important local routeway at this time, for negotiating the bogs which would have been even wetter early in their developments.
C. Bogs
While bogs are obstacles, they are not necessarily impen- etrable if one is prepared to invest energy in the construc- tion of a trackway. Archaeological evidence [4], [5], [6] has revealed a series of timber trackway constructions in these wetland locations, suggesting that there were incentives to traversing the bog, rather than diverting around it using dry land. The principle incentive would have been the saving of time and energy by significantly shortening a journey. Typi- cally, trackways traverse the bog at narrow points, although exceptions exist which are speculated to be for ritual pur- poses or to access resources within the bog. This means the trackways can be divided into two categories, those crossing the bog which treat it as an obstacle, and those accessing the bog which treat it as an objective.
D. Hills and Rises
The terrain throughout the study area is relatively flat, ranging from 40m OD around the River Shannon basin in the West, to 90m in the East. Apart from the extinct volcano at Croghan Hill, with a height of 220m, most rises are quite low, but nevertheless highly visible. These rises often mark the narrowest crossing point across bogs, and they offer a visual cue to anyone traversing the landscape, as well as an ideal vantage point to gauge the terrain ahead.
E. The Slighe Mór
Documentary itineraries survive which tell us the names of settlements where the Slighe Mór passed [9]. Within the study area, it is known to have passed through Rhode, Croghan, Kiltober, Durrow, Ballycumber, Togher, Bal- laghurt and Clonmacnoise. For most of these locations, early ecclesiastical sites have been chosen as nodes between which the models are run.
III. METHODOLOGY
A. Data
The map for the study area was produced using Copernicus data and information funded by the European Union – EU-DEM layers, with soil information from the Soils and Subsoils Database from the Environmental Protection Agency. Road data is © OpenStreetMap and Contributers, CC-BY-SA and the Record of Monumements and Places is
© Department of Arts, Heritage and the Gaeltacht. I am grateful to Conor McDermott, University College Dublin, for providing survey data from the Irish Archaeological Wetland Unit.
B. Least Cost Paths
The natural features which create potential routeways or obstacles in this landscape are characterised by soil type more so than slope. The Weighted Overlay tool was used to give soil type a weighting of 75% and slope a weighting of 25% to produce a Cost Surface. A scale value of 1 to 10 was applied to each soil type with the following hypothetical values;
Cutover peat – 10 Limestone till – 2
Limestone sands and gravels – 2 Basic esker – 1
Alluvium – 8 Rock – 6 Fen peat – 10 Water – 10
Lake sediment – 10 Made ground – 4 Sandstone till – 2 Marl – 6
Karstified limestone – 6
ArcGIS Least Cost Paths are anisotropic, meaning they are direction dependent. As such, each segment was run in both directions in order to gauge the effect of direction on movement. A realistic path ought to be a hybrid of both of
Fig 1: Location of study area
these paths, but it is not unusual to take a different route de- pending on direction of travel. Even in the case of estab- lished roads, pedestrians often take a different route to and from a location to avoid particular slopes or to maintain a straight course for as long as possible before changing course. It was thus decided to record both results.
C. Agent-Based Modelling
The NetLogo GIS extension was used to import the rele- vant shapefiles to the model, including soil types and eleva- tion data. This model was similarly run in both directions to gain a fuller understanding of the effect of direction on movement. A set number of agents, or turtles in NetLogo terminology, are created at one settlement which is known to have been on the Slighe Mór and told their target is the next settlement.
The leading turtle, or leader breed, turns its heading to its target. Since these settlements are next to significant landscape features such as hills, it was deemed realistic to set a heading in this way from the beginning of the journey, as a traveller in reality would use the hills as visual cues.
After setting its heading, the turtle must then negotiate the landscape using a series of simple instructions.
Booleans were used to differentiate between obstacle and not obstacle, with bogs acting as obstacles. When a bog is encountered, the turtle is obliged to find a suitable crossing point by using the in-cone reporter which emulates visual perception in reality to find dry land within a set dis- tance and radius. With this code, the leading turtle can find the most efficient crossing point within a reasonable dis- tance without having to circle the entire bog.
Slope was also considered, with instructions to turn the heading towards the patch with least slope within 2 patches.
In this way, steep climbs are avoided and minor corrections are made as the more problematic obstacles are negotiated.
All subsequent turtles, known by the follower breed, are released at regular intervals and they have the same ca- pabilities as the leader to solve any obstacles encoun- tered. They have the advantage, however, of having already had the problem solved by the leader, albeit in an ineffi- cient way. Using the same method as the Ant Lines model [8], each follower turns its heading to its immediate prede- cessor, while still running its own code to negotiate obsta- cles and manage slope. This has the effect of smoothing the path over time. Rather than maintaining a heading from the beginning to the opposite settlement, turtles later in the se- quence aim straight towards the first solution to an obstacle.
This cumulative process approaches an efficient path, as ev- ident from the final turtle matching quite closely the path created through Least Cost Paths.
IV. RHODETO CROGHAN
A. Landscape
The settlements of Rhode and Croghan in northeast Co.
Offaly occupy slight elevations which are surrounded by a series of hills of volcanic origin and are separated by Bally- beg Bog (Fig. 2). O’ Lochlainn [9] tells us that the Slighe Mór linked these two settlements in the Early Medieval pe- riod, so a routeway must have existed between them despite the obstacle of the bog. Clonin Hill, which overlooks Rhode, is topped with a substantial Bronze Age ring barrow, while Croghan Hill is the location of an extremely prominent burial mound. The dating of this monument is uncertain, but the lack of an external ditch would suggest that it is a Neolithic cairn, rather than a Bronze Age barrow. Within the bog itself, the remains of Bronze age settlement and mi- nor trackways which are not designed to cross the bog have been recovered in wetland survey of the area [10], [11]. The presence of prehistoric archaeology at these locations sug- gests prolonged use of this landscape, which would have re- quired a routeway connecting these sites at an even earlier date than the Slighe Mór is usually dated to.
B. Least Cost Path Results
The Least Cost Paths predictably traverse the bog at the narrowest point (Fig. 3). This point is flanked by Madam’s Hill in Toberdaly, east of the bog, and Barrysbrook Hill to the west. The paths skirt around the lowest slopes of each of these hills avoiding as much as possible the patches of ground with bedrock at the surface, which have a relatively
Fig 2: Rhode to Croghan
high value on the weighted overlay, and which tend also to have increased slope values.
C. Agent-Based Modelling Results
A direct path from Rhode to Croghan and vice versa would traverse Ballybeg Bog at an unsuitable crossing point, so the leading turtle is obliged to search for a nar- rower point, which it finds between Toberdaly and Barrys- brook, just as Least Cost Paths found (Fig. 4). Each follower is able to shorten the path to the crossing point, leading to an eventual path which makes straight for the crossing, with minor corrections made for slope. With the bog cross- ing complete, the remainder of the trip is unimpeded and a relatively straight route can be taken to the objective.
D. Archaeological Evidence
This path taken by both programs through Ballybeg Bog coincides with the existing roadway which crosses this ob- stacle. A map dating to c. 1563 (Fig. 5) illustrates this crossing point, a causeway between Cnocarderin and a se-
ries of hills East of Croghan. The feature is labelled as a togher and defended by a castle, demonstrating the strategic importance of this crossing. The Togher of Croghan, or Tóchar Cruachain Brí Éile, is mentioned in the Annals at least as early as 1385, so the current roadway, and the path suggested by the modelling, mark a crossing of some antiq- uity. Given the prehistoric archaeology in the area, it would be likely that this crossing would have been exploited at an earlier date also.
The section of road linking the togher with Croghan is 19th century in date but it matches the path predicted by both modelling procedures and happens to have been flanked by two standing stones. An older road circles south of Barrysbrook Hill, before meeting a crossroads which can be taken back towards Croghan. When walking this route- way, it is clear that the series of hills which make up this landscape (Clonin Hill, Madams Hill, Barrysbrook Hill and Croghan Hill) create visual cues which one aims towards when navigating the terrain. In particular, the target gener- ally seems to be towards a low point on the slope, offering a suitably dry area for comfortable walking without an unnec- essarily high climb, and providing an ideal vantage point to view the ground ahead. With this in mind, it would make no sense to move south of Barrysbrook Hill to reach Croghan.
This path would only make sense if one was bypassing Croghan in favour of Kilclonfert, another ecclesiastical set- tlement which was reputedly on the Slighe Mór [12].
This author would suggest that the standing stones, the models and the trajectory which the landscape impresses on a traveller through visual cues is sufficient to seriously con- sider the presence of an older routeway between Barrys- brook Hill and Croghan Hill. Perhaps any earlier routes through Croghan Demesne would have been discouraged – it is clear that older road south of Barrysbrook Hill skirts around the grounds of the townland of Croghan Demesne.
Fig 5: Togher of Croghan. With permission © The British Library Board. Cotton Augustus MS I ii 40. North to right
of image.
Fig 3: Rhode to Croghan Least Cost Path
Fig 4: NetLogo model - Rhode to Croghan
V. CROGHANTO KILTOBER
A. Landscape
Kiltober townland is largely composed of limestone sands and gravels with the very substantial Rahugh esker creating the southeastern border (Fig. 6). This is a particularly sig- nificant part of the Slighe Mór as it marks an intersection with the Midland Corridor. The importance of this intersec- tion is demonstrated by the distribution of barrows in pre- history and ringforts in the medieval period, with particular emphasis on areas with limestone sand and gravel subsoil.
Clonearl Bog and Raheenmore Bog are located between Croghan and Kiltober, and these must be negotiated to move between the settlements. Just as in the previous seg- ment, a series of low hills are present at Oldcroghan, Kil- duff, Clonagh and Mullagharush Hill and they mostly flank the narrowest points of the bogs.
B. Least Cost Path Results
The Least Cost Paths for this segment similarly traverse the bogs at the narrowest points available without deviating course more than a few degrees (Fig. 6). Clonearl Bog is crossed at a narrow point on its northern extent, between rises at Oldcroghan and Kilduff. Raheenmore Bog narrows to only 10m East of Clonagh Hill, and the paths skirt the southern base of that rise and Mullaghrush Hill. The hills mark the most convenient crossing points, but they are only climbed as much as is necessary to gain dry land. The esker is climbed at a suitably gentle point on its northeastern ex- tent, after which this level, single-crested esker leads di- rectly to the Kiltober.
C. Agent-Based Modelling Results
The journey from Croghan to Kiltober requires the cross- ing of Clonearl Bog and Raheenmore bog (Fig. 7). The leader finds the narrowest points in these bogs, which is
exactly the same point which Least Cost Paths identified as the most efficient route. The model differs significantly from the ArcGIS version on the Western extent where the esker is accessed. The model does not give preference to the esker and climbs it c. 1km South of the Least Cost Path. This es- ker has been used as a road, with two castles situated along its course, one being a motte and bailey castle which dates to the late 12th or early 13th century, suggesting lengthy use of this esker as a road. It is clear then that eskers are more important in the placement of roads than slope alone would suggest. This is down to their elevation and the composition of the subsoils, which are well-drained and ideal for use as a pathway. This supports the preferential weighting given to eskers in the Weighted Overlay in ArcGIS.
D. Archaeological Evidence
Clonearl Bog is most recognised for the Iron Age bog body found there in 2003. Oldcroghan Man, as he is known, was found 1.3km Southeast of the proposed crossing, where the bog is at its widest. As discussed above (II D), activities in the bog can be separated between those which treat the bog as an obstacle and those which treat it as an objective.
The deposition of Oldcroghan Man was a ritual activity and it is no surprise that it should take place in a different loca- tion to simple negotiation of an obstacle, but it is a good in- dication for activity in the environment, from which we can assume movement was taking place.
The predicted paths closely correlate with existing roads at the Raheenmore Bog crossing and along the southern slopes of Clonagh and Mullagharush Hill (Fig. 8). While the existing road climbs the esker 0.5km South of the Least Cost Path prediction, they maintain a very similar course to the target.
A standing stone and several barrows are in close prox- imity to the esker on its west side. These are part of the cluster of barrows which mark where the Midland Corridor enters into the ancient kingdom of Leinster and are more closely associated with that route rather than the esker. With
Fig 6: Croghan to Kiltober Least Cost Path
Fig 8: Croghan to Kiltober
only a few exceptions however, this esker delimits the ex- tent of this distribution. The orientation of this esker is un - usual as most examples in Offaly are of an east-west orien- tation. This unusual esker is therefore acting as a wrapping mechanism, delimiting the Midland Corridor and the bar- row distribution, as well as representing the crossing point of two important routeways.
VI. DISCUSSION
Those natural features which are conducive to movement must be exploited and established in the mental map of in - dividuals before they can truly be called routeways. While ArcGIS can effectively show us the end product and a po- tential routeway, NetLogo shows how routeways are estab- lished through a series of discrete actions around those nat- ural features, acted out by individual agents over time. The ability of agents to effectively learn from their predecessors through the use of the Ant Lines model, allows for quicker problem-solving on the part of the individual and more effi- cient paths than initial attempts would produce.
In real world problem-solving, this would appear as a se- ries of trails which impress upon any subsequent traveller. If an opportunity arises to smooth the trail through cutting corners it is usually done, as is evident in the elaborate net- work of desire lines which can be seen in managed park- lands or city green areas. The most efficient path becomes the most established one both mentally, through repeated experiences, and physically, through repeated use and per- haps even enhancement through construction. In this way, a stable macrostructure emerges from the interaction of local agents and feedback from microstructures [1].
Both Agent-Based Modelling and Least Cost Paths reflect different facets of the theoretical approach of this research.
Complex systems can be derived from a variety of factors involving simple rules and no centralised control. Energy and physical factors which GIS handle so well are crucial in this, but experiential concerns and other qualitative factors ought also to be considered in the emergence and develop- ment of routeways and subsequent networks.
VII. CONCLUSION
The use of these methodologies allows us to not only hy- pothesise the position of paths in the landscape, but to un- derstand the processes which lead to their creation. Having done so, we can compare predicted paths with existing roads to identify the locations which merit further research archaeologically. Archaeological monuments in proximity to these paths can be better understood as part of their over- all landscape by understanding how they fit into the exist- ing system of routeways. The segments discussed have in- cluded portions which were important enough to have war- ranted castles to protect them, such as the Togher of Croghan, while the presence of prehistoric archaeology throughout each example demonstrates the necessity of routeways from the earliest settlement in this area. Viewing these monuments in a movement-centric framework has helped to place them into the context they would have been experienced in the past.
REFERENCES
[1] J. M. Epstein, Growing Artificial Societies: social science from the bottom up. Brookings Institution Press, 1996.
[2] U, Wilensky, NetLogo, http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modelling, Northwestern University, Evanston, IL, 1999.
[3] M. Tubridy and R. Meehan, County Offaly Esker Survey 2006. Offaly County Council, 2006.
[4] B. Raftery, Trackway Excavations in the Mountdillon Bogs, Co.
Longford, 1985-1991. Dublin: Crannóg Publications, 1996.
[5] J. Whitaker and E. O’ Carroll, Peatland Excavations 1999-2000:
Lemanaghan Group of Bogs, Co. Offaly. Dublin: Archaeological Development Services, 2009.
[6] J. Whitaker, Peatland Excavations 2001-2002: Mountdillon Group of Bogs, Co. Longford. Dublin: Archaeological Development Services, 2009.
[7] A.P. Smyth, Celtic Leinster: towards an historical geography of early Irish civilisation, AD 500-1600. Dublin: Irish Academic Press, 1982.
[8] U. Wilensky, NetLogo Ant Lines model,
http://ccl.northwestern.edu/netlogo/models/AntLines. Center for Connected Learning and Computer-Based Modelling, Northwestern University, Evanston, IL, 1997.
[9] C. O’ Lochlainn, “Roadways in Ancient Ireland”, in Féil Sgríbinn Éoin Mhic Néill. Dublin: 1940, pp. 465-474.
[10] C. Murray, ‘Ballybeg Bog, Barrysbrook/ Clonin/ Toberdaly/ Togher’, http://www.excavations.ie/Pages/Details.php?
Year=&County=Offaly&id=7044, Dublin: Wordwell.
[11] J. Whitaker, ‘Lanespark, Ballybeg and Derryvella Bogs, Derryvella/
Glengoole North/ Lanespark/ Poynstown’
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[12] E. Fitzpatrick and C. O’ Brien, The Medieval Churches of County Offaly. Ireland: Government of Ireland, 1998.
Abstract—This paper aims to evaluate notions of two crucial studies on the Roman economy by Bang and Temin based on the study of distribution patterns of ceramic tablewares in the Roman East in the period 150BCE-200CE. It presents an agent- based network model simulating the social networks which represent the flow of information and goods between traders.
Results of the simulation are subsequently compared to the tableware data collected in the ICRATES database.
Preliminary results suggest, contrary to Bang’s hypothesis, that limited availability of reliable commercial information from different markets is unlikely to give rise to the large differences in the wideness of product’s distributions observed in the archaeological record.
I. INTRODUCTION
eramic tableware is one of the most common find cate- gories on Roman sites in the Eastern Mediterranean and therefore lends itself particularly well to quantification. It of- fers archaeologists a key tool for approaching aspects of the ancient economy. One of the most robust patterns observed in the collected tableware data is the variability of distribu- tion patterns of different tablewares at consumption sites (products characterised by a distinct clay fabric and pro- duced in different centres). Some wares such as Eastern Sig- illata A (ESA) were distributed on a supra-regional scale for centuries, others were more of regional importance (Eastern Sigillatas B, C, and D), whilst yet other wares were produced for local consumption. What were the mechanisms that led to differences in the wideness of products’ distribution patterns? A number of hypotheses have been published iden- tifying, coupling and balancing particular combinations of possible contributing factors, such as state involvement, re- distributive centres, consumption “pulling forces”, commer- cial “piggy-back” trade, closeness to large-scale agricultural production, connectivity, etc. [1]-[4]. Most scholars seem to agree that a complex mix of mechanisms working on multi-
C
The ICRATES project was supported by the Belgian Programme on Interuniversity Poles of Attraction (IAP 07/09), the Research Fund of the University of Leuven (BOF-GOA 13/04), Project G.0562.11 of the Research Council-Flanders (FWO) and the Hercules Foundation (AKUL/09/16).
ple levels was responsible for the considerable differences in tableware distribution patterns. Since there is evidently no lack of hypotheses, the main challenge becomes to recognise the mix of contributing factors that is best supported by the available evidence, and finding a more quantitative approach that allows one to distinguish between the archaeological
“signatures” of different hypothetical scenarios. The devel- opment of such approaches has so far been limited in Roman studies [5]-[6].
This paper aims to contribute to this on-going discussion by evaluating two hypotheses of the role of social networks in tableware trade and distribution. It uses a combination of an exploratory analysis of the collected tableware data from the Roman East between 150BCE and 200CE (using the ICRATES database of tablewares) with computational mod- elling of hypothetical trade mechanisms.
In this paper we will focus our efforts on exploring the po- tential role of social networks as a driving force of the Ro- man trade system. The concept of social networks is here used as an abstraction of the commercial opportunities of traders, acting as a medium for the flow of information and products. We aim to formalise and evaluate aspects of two models of the Roman trade system in which such social net- works play a key role: Peter Bang’s The Roman Bazaar [7]
and Peter Temin’s The Roman Market Economy [8]. Bang considers three factors as crucial to understanding trade and markets in Roman Imperial times: bazaar-style markets, the tributary nature of the Roman Empire, and the agrarianate nature of ancient societies. The engine of the model, howev- er, is clearly the concept of the bazaar: the existence of local markets characterised by a high uncertainty of information, and relative unpredictability of supply and demand. This lim- ited availability of commercial information led to poorly in- tegrated markets throughout the empire. Bang argues that different trajectories for the flow of goods could emerge as the result of different trajectories for the flow of information.
In other words, the observed distribution patterns of table- wares and different workshops’ products (when these can be identified) were at least in part a reflection of the structure and functioning of past social networks as defined above.
Roman Bazaar or Market Economy? An Agent-based Network Model of Tableware Trade and Distribution in the Roman East
Tom Brughmans
Sagalassos Archaeological Research Project, University of Leuven
Department of Computer and Information Science, Universität Konstanz
Email: Tom.Brughmans@uni-konstanz.de
Jeroen Poblome
Sagalassos Archaeological Research Project, University of Leuven
Email: Jeroen.Poblome@arts.kuleuven.be
