DOCSLIB.ORG

The 20Th International Workshop on Multi-Agent-Based Simulation

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The 20Th International Workshop on Multi-Agent-Based Simulation The 20th International Workshop on Multi-Agent-Based Simulation MABS 2019 Montreal, Canada May 13, 2019 PROGRAM CHAIRS • Jaime Simão Sichman (University of São Paulo, Brazil) • Mario Paolucci (ISTC, Italy) • Harko Verhagen (Stockholm University, Sweden) THE MABS STEERING COMMITTEE • Frédéric Amblard (University of Toulouse, France) • Luis Antunes (University of Lisbon, Portugal) • Paul Davidsson (Malmö University, Sweden) • Nigel Gilbert (University of Surrey, UK) • Tim Gulden (George Mason University, USA) • Emma Norling (Manchester Metropolitan University, UK) • Mario Paolucci (National Research Council, Italy) • Jaime Simão Sichman (University of São Paulo, Brazil) • Takao Terano (Tokyo Institute of Technology, Japan) PROGRAM COMMITTEE • Diana Adamatti (FURG, Brazil) • Frederic Amblard (Université Toulouse 1, France) • Luis Antunes (University of Lisbon, Portugal) • Tina Balke (Vanderlande Industries, The Netherlands) • Joao Balsa (University of Lisbon, Portugal) • Federico Bianchi (University of Brescia, Italy) • Cristiano Castelfranchi (ISTC-CNR, Italy) • Sung-Bae Cho (Yonsei University, Korea) • Paul Davidsson (Malmö University, Sweden) • Frank Dignum (Utrecht University, the Netherlands) • Graçaliz Pereira Dimuro (FURG, Brazil) • Bruce Edmonds (Centre for Policy Modelling, UK) • Francisco Grimaldo (University of Valencia, Spain) • Laszlo Gulyas (University of Budapest, Hungary) • Rainer Hegselmann (University of Bayreuth, Germany) • Marco Janssen (Arizona State University, USA) • Jean-Pierre Muller (CIRAD, France) • Luis Gustavo Nardin (Brandenburg University of Technology, Germany) • Emma Norling (University of Sheffield, UK) • Paulo Novais (Universidade do Minho, Portugal) • Mario Paolucci (ISTC-CNR, Italy) (co-chair) • William Rand (North Carolina State University, USA) • Juliette Rouchier (CNRS/LAMSADE), France) • Jaime Sichman (University of Sao Paulo, Brazil) (co-chair) • Samarth Swarup (University of Virginia, USA) • Klaus Troitzsch (University of Koblenz, Germany) • Natalie Van der Wal (Vrije Universiteit Amsterdam, the Netherlands) • Harko Verhagen (Stockholm University, Sweden) (co-chair) • Neil Yorke-Smith (Delft University of Technology, The Netherlands) CONTENTS MABS and Policy Modelling policy shift advocacy Antoni Perello-Moragues, Pablo Noriega, Lucia Alexandra Popartan and Manel Poch Reinforcement Learning of Supply Chain Control Policy using Closed Loop Multi-Agent Simulation Souvik Barat, Harshad Khadilkar, Vinay Kulkarni, Vinita Baniwal, Hardik Meisheri, Monika Gajrani and Prashant Kumar Agent based simulation of the dengue virus propagation Letícia da Silva Rodrigues, Sóstenes Gutembergue Mamedio Oliveira, Luiz Fernandez Lopez and Jaime Simão Sichman Modeling Pedestrian Behavior Under Panic During a Fire Emergency Juhi Singh, Atharva Deshpande and Shrisha Rao MABS and Social Artifacts An opinion diffusion model with deliberation George Butler, Gabriella Pigozzi and Juliette Rouchier Agents with Dynamic Social Norms Samaneh Heidari, Nanda Wijermans and Frank Dignum A collective action simulation platform Stephen Cranefield, Hannah Clark-Younger and Geoff Hay MABS Foundations Constructing an Agent Taxonomy from a Simulation through Topological Data Analysis Samarth Swarup and Reza Rezazadegan On Developing A More Comprehensive Decision-Making Architecture for Empirical Social Research: Agent-Based Simulation of Mobility Demands in Switzerland Khoa Nguyen and René Schumann Complexity metrics for Agent Based Models of Social Systems Kiran Lakkaraju, Asmeret Naugle, Laura Swiler, Stephen Verzi and Christina Warrender Modelling policy shift advocacy Antoni Perello-Moragues1,2,3, Pablo Noriega2, Lucia Alexandra Popartan4, and Manel Poch4 1 Aqualia, Spain 2 IIIA-CSIC, Barcelona, Spain tperello, pablo @iiia.csic.es { } 3 Universitat Aut`onoma de Barcelona, Spain 4 LEQUIA, Universitat de Girona, Spain luciaalexandra.popartan, manuel.poch @udg.edu { } Abstract. In this paper, we propose to enrich standard agent-based so- cial simulation for policy-making with an a↵ordance inspired by second- order emergent social phenomena. Namely, we explore the inclusion of agents who have means to perceive, aggregate and respond to emergent collective outcomes and demand political intervention. Given this pur- pose, we work on a subclass of socio-cognitive technical systems that we called value-driven policy-making systems. We inspire and illustrate our proposal with a model of urban water management. Keywords: agent-based social simulation socio-cognitive technical sys- · tems policy-making values second-order emergent phenomena · · · 1 Introduction Agent-based social simulation (ABSS) has been shown to be appropriate tool for policy-making [5]. Nonetheless, it has been suggested that in order to increase the usability for policy-making, standard ABSS may be enriched with some specific socio-cognitive a↵ordances [11]. In this spirit, we proposed to a↵ord some type of ethical reasoning and means to promote and assess moral behaviour [13]. The rationale being that, on the one hand, policy-makers draw on their political views and principles to design a policy intended to bring about a better state of the world, and deploy policy instruments that are consistent with such aim; and on the other hand, those agents who are subject to one such policy act according to their own principles, interests and motivations [17,3]. With this claim in mind, we characterised a type of agent-based simulators of public policies, as a subclass of socio-cognitive technical systems (SCTS) [9], that we called value-driven policy-making systems. They involve values as a first class notion and propose their operationalisation through policy-schemas,which consist of sets of policy means and policy ends [13]. In this paper, we extend that work with an a↵ordance that we find specially relevant in some policy domains; namely, means to perceive, aggregate and re- spond to emergent collective outcomes. This a↵ordance is inspired by the notion 2 A. Perello-Moragues, P. Noriega, L.A. Popartan and M. Poch second-order emergent social phenomena (EP2) [11,4]. In order to illustrate our proposal, we model the management of urban water and, more specifically, the interplay between influential stakeholders (e.g. political factions) and their target groups in the process of advocating policy changes. For these purposes, we start with a brief overview of our previous work and the type of second order phenomena simulation we propose (Sec. 2). In Sec. 3 we outline the core components of the enhanced framework. In Sec. 4 we present a model of the example and discuss some results. We close with remarks on further work (Sec. 5). 2 Background Our aim is to define a framework for the simulation of second-order social phe- nomena in a sub-class of SCTS that have been characterised as value-driven policy-making systems (VDPMS) [13]. We build on the following ideas: 1. Socio-cognitive technical system (SCTS) are situated, on-line, hy- brid, open regulated multi-agent systems [9]. They are composed by two first class entities: a social space and participating agents, who have socio-cognitive (opaque) decision models that guide their actions. In previous work [13], we explored the role of values in the regulation of the social space and in the decision-making of agents. We proposed a core meta- model for that class that includes five components that we discuss in more detail in Sec. 3: (i) At least two agent roles;(ii)Apolicy-schema composed of means —that aim to produce a behavioural change on policy-subjects so as to drive the system towards a desirable world-state— and ends —that define those desirable world-states; (iii) A finite set of values that are projected onto the policy-schema; and (iv) Satisfaction functions for agents. In addition, we assumed that policy-making presumes a socio-ecological con- text that determines the relevant part of the physical world and a policy domain that informs values, policy-schemas and satisfaction functions (Fig. 1). 2. Values. We assume a cognitive notion of value that may be used to model value-based reasoning for individuals, and value-based assessment of a state of the world [8,12,7,16,19]. Thus, we assume that values have the following six properties [16]: (P1): Values are beliefs; (P2): Values refer to desirable goals; (P3): Values serve as standards or criteria; (P4): Values are ordered by impor- tance; (P5): The relative importance of multiple values guides action; (P6): Val- ues transcend specific actions. 3. Second order emergence social phenomena (EP2 )referstotheidea that agents may recognise an emerging macro-phenomenon and, as a conse- quence, they may intentionally support or hinder the phenomena or the emerg- ing process itself [4,14,11]. Castelfranchi [4] approached EP2 as the cognitive emergence of the macro-phenomena in the agent’s mind, and afterwards a pro- cess of cognitive immergence that changes its behaviour. He discusses examples where the awareness of the phenomenon can promote or discourage it (e.g. urban segregation, ghetto formation). Other examples can be found in [11,18]. Modelling policy shift advocacy 3 Fig. 1: Distinctive features of policy-making as a value-driven socio-cognitive system [13] 3 A conceptual framework Due to space limitations, we cannot go into the detail needed to have a formal metamodel to represent SCTS with an appropriate level of accuracy. Nonetheless, we work on the basic components used in social coordination frameworks [1] and VDPMS [13], such as socio-economic environment, values
Load more

Recommended publications
  • Varieties of Emergence
    See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/228792799 Varieties of emergence Article · January 2002 CITATIONS READS 37 94 1 author: Nigel Gilbert University of Surrey 364 PUBLICATIONS 9,427 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Consumer Behavior View project Agent-based Macroeconomic Models: An Anatomical Review View project All content following this page was uploaded by Nigel Gilbert on 19 May 2014. The user has requested enhancement of the downloaded file. 1 VARIETIES OF EMERGENCE N. GILBERT, University of Surrey, UK* ABSTRACT** The simulation of social agents has grown to be an innovative and powerful research methodology. The challenge is to develop models that are computationally precise, yet are linked closely to and are illuminating about social and behavioral theory. The social element of social simulation models derives partly from their ability to exhibit emergent features. In this paper, we illustrate the varieties of emergence by developing Schelling’s model of residential segregation (using it as a case study), considering what might be needed to take account of the effects of residential segregation on residents and others; the social recognition of spatially segregated zones; and the construction of categories of ethnicity. We conclude that while the existence of emergent phenomena is a necessary condition for models of social agents, this poses a methodological problem for those using simulation to investigate social phenomena. INTRODUCTION Emergence is an essential characteristic of social simulation. Indeed, without emergence, it might be argued that a simulation is not a social simulation.
    [Show full text]
  • Nigel Gilbert the Middle
    Simulating social phenomena: the middle way Nigel Gilbert University of Surrey Guildford UK http://cress.soc.surrey.ac.uk Centre for Research in Social Simulation Thursday, June 24, 2010 1 Agents • Distinct parts of a computer program, each of which represents a social actor • Agents may model any actors – Individuals – Firms – Nations – etc. • Properties of agents ✦ Perception ✦ Performance ✦ Policy ✦ Memory 2 Centre for Research in Social Simulation Thursday, June 24, 2010 2 Interaction • Agents are not isolated • Information passed from one agent to another ✦ (coded) Messages ✦ Direct transfer of Knowledge ✦ By-products of action e.g. chemical trails or pheromones ✦ Etc. 3 Centre for Research in Social Simulation Thursday, June 24, 2010 3 Environment • Options: ✦ Geographic space ✦ Analogues to space e.g. knowledge space ✦ Network (links, but no position) • The environment provides ✦ Resources ✦ Communication 4 Centre for Research in Social Simulation Thursday, June 24, 2010 4 An example: modelling the housing market • Hugely important to national economies ✦ in UK, NL, ES, US etc. • Housing in these countries is a major component of personal wealth, as well as just a place to live ✦ affecting consumption, inheritance, mobility etc. • A special market ✦ location important ✦ infrequent purchase ✦ many parties • buyer, seller, • estate agent/realtor, • bank 5 Centre for Research in Social Simulation Thursday, June 24, 2010 5 Previous work IV – Outlook for the UK housing market Introduction Figure 4.1 - Average UK house price 1974Q1-2007Q3 Average UK house price (£) • Mostly econometric models Housing continues to be the UK economy’s 200000 most valuable asset by far. Housing was 180000 ✦ estimated by the Office for National 160000 Statistics to have a total value of £3.9 trillion used to produce quantitative house price 140000 at the end of 2006, equivalent to 60% of the 120000 total value of all UK assets (valued at some 100000 projections £6.5 trillion).
    [Show full text]
  • Resume Nigel Gilbert Sociology, University of Surrey
    Resume Nigel Gilbert Sociology, University of Surrey Professor Nigel Gilbert is Professor of Sociology at the University of Surrey. He has an international reputation as a pioneer in the use of computer simulation in the social sciences and is the author of the principal textbook in that field and many research papers. He is immediate past President of the European Social Simulation Association and founder-editor of the Journal of Artificial Societies and Social Simulation. He has held a personal Chair at Surrey since 1991. From 1997 to 2005, Professor Gilbert was a Pro Vice-Chancellor of the University of Surrey, apart-time post. He had strategic responsibility for staffing matters and was a member of thesenior management team of the University, a chartered institution with a turnover approaching £150 million and 13,000 students. His research interests encompass the sociology of scientific knowledge (understanding howscientists generate reliable knowledge), science policy (strategies for the management of science),and the sociology of the environment, including the management of natural resources such as water. He has written extensively in these areas and is the editor of one of the textbooks on sociological research methods most widely used in UK universities. He has a first degree in Engineering Science from Cambridge. Since graduation, he has aimed to link engineering and the social sciences and his work was honoured with election as a Fellow of the Royal Academy of Engineering in 1999. He is still the only practicing social scientist to be a Fellow of the Royal Academy. He was President of the Engineering Section of the British Association for the Advancement of Science in 2005 and is at present leading a policy group for the Royal Academy on privacy and surveillance.
    [Show full text]
  • Aviso De Conferencia
    AAVISO DE CCONFERENCIA QLectives: evolving software to support quality Prof. Nigel Gilbert. Centre for Research in Social Simulation, University of Surrey (United Kingdom) Facultad de Informática Aula 14 6 de junio de 2012 16: 30 entrada libre hasta completar el aforo resumen: In this talk, I'll summarise current progress in the FP7 Integrated Project, QLectives, which aims to develop software that will assist collectives (e.g. scientific specialties, photo-sharing groups, political activist groups) self-organise into communities that support the distribution of high quality self-generated content. The project starts from a complexity science theoretical perspective and aims to build tools that are fully distributed, preserve privacy and require no central control or authority. Some of the challenges of running such an inter-disciplinary endeavour with ambitious and possibly unattainable goals will be described, as well as the directions in which the project is going and what we expect to produce by the end of the project in one year's time. sobre Niger Gilbert: Nigel Gilbert is Professor of Sociology at the University of Surrey, with an interdisciplinary background in Engineering and Social Sciences. He is Director of the Centre for Research on Simulation in the Social Sciences (CRESS), Director of the Institute of Advanced Studies and founder and Editor of the Journal of Artificial Societies and Social Simulation, main journal in the field. He has directed or participated in multiple European Projects (IMAGES, SEIN, FIRMA, SIMWEB, EMIL, NEMO, NEWTIES, PATRES, etc). He is a Fellow of the Royal Academy of Engineering, Fellow of the British Computer Society, the Royal Society of Arts, and the Academy of the Social Sciences.
    [Show full text]
  • Simulation for the Social Scientist
    GilbertTroit005pb17.5.qxd 1/27/2007 10:52 AM Page 1 second second edition edition Simulation for the Social Scientist SIMULATION FOR THE SOCIAL SCIENTIST Simulation Second Edition • What can computer simulation contribute to the social sciences? • Which of the many approaches to simulation would be best for my social science project? for the • How do I design, carry out and analyse the results from a computer simulation? Interest in social simulation has been growing rapidly worldwide as a result of increasingly powerful hardware and software and a rising interest in the Social application of ideas of complexity, evolution, adaptation and chaos in the social sciences. Simulation for the Social Scientist is a practical textbook on the techniques of building computer simulations to assist understanding of social and economic issues and problems. Scientist This authoritative book details all the common approaches to social simulation to provide social scientists with an appreciation of the literature and allow those with some programming skills to create their own simulations. New for this edition: • A new chapter on designing multi-agent systems to support the fact that multi-agent modelling has become the most common approach to simulation • New examples and guides to current software • Updated throughout to take new approaches into account The book is an essential tool for social scientists in a wide range of fields, particularly sociology, economics, anthropology, geography, organizational theory, political science, social policy, cognitive psychology and cognitive science. It will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies. Gilbert • Troitzsch Nigel Gilbert is Professor of Sociology at the University of Surrey, UK.
    [Show full text]
  • Expertise As an Object: an Ontological Study of Cryptology Research in the United Kingdom from 1970 to 2000
    UNIVERSITY OF SURREY Expertise as an Object: An Ontological Study of Cryptology Research in the United Kingdom from 1970 to 2000 by Richard Fletcher Submitted for the degree of Doctor of Philosophy Faculty of Arts and Human Sciences Department of Sociology Supervisors: Dr Christine Hine and Dr Nicola Green ©Richard Fletcher Words: 95,698 Declaration of Authorship This thesis and the work to which it refers are the results of my own efforts. Any ideas, data, images or text resulting from the work of others (whether published or unpublished) are fully identified as such within the work and attributed to their originator in the text, bibliography or in footnotes. This thesis has not been submitted in whole or in part for any other academic degree or professional qualification. I agree that the University has the right to submit my work to the plagiarism detection service TurnitinUK for originality checks. Whether or not drafts have been so-assessed, the University reserves the right to require an electronic version of the final document (as submitted) for assessment as above. Signature: Date: i \Quis custodiet ipsos custodes?" Juvenal (Satire VI, lines 347-8) Abstract Recent research carried out under the `third wave of science studies' has produced robust categories of expertise, and has developed normative ideas about how it should be used during controversies over technological decision-making. Though separate in the literature, third wave ideas about contributory expertise appear to be compatible with the recent `turn to ontology'. Both sets of ideas focus on what it is that practices are able to produce, and consider the results of those practices to be real.
    [Show full text]
  • 6Th Conference of the European Social Simulation Association
    6th Conference of the European Social Simulation Association (ESSA 2009) Guildford, United Kingdom 14-18 September 2009 Editors: Bruce Edmonds Nigel Gilbert ISBN: 978-1-63439-623-3 Printed from e-media with permission by: Curran Associates, Inc. 57 Morehouse Lane Red Hook, NY 12571 Some format issues inherent in the e-media version may also appear in this print version. Copyright© (2009) by the European Social Simulation Association (ESSA) All rights reserved. Printed by Curran Associates, Inc. (2015) For permission requests, please contact the European Social Simulation Association (ESSA) at the address below. European Social Simulation Association (ESSA) c/o University of Surrey GU2 7XH United Kingdom Phone: +441483300800 [email protected] Additional copies of this publication are available from: Curran Associates, Inc. 57 Morehouse Lane Red Hook, NY 12571 USA Phone: 845-758-0400 Fax: 845-758-2634 Email: [email protected] Web: www.proceedings.com Table of Contents Invited Talks The Creativity of the Evolution of Technology Is a Target for Social Simulation Efforts ....................................................... N/A Mark Bedau Does ABSS need Cognitive Agents that are Multiple Agent Systems? .......... 1 Jim Doran Generative Archaeology: How even really simple models can help in understanding the past .................................................. 2 Tim Kohler Plenary Presentations The Simplicity of Cooperation: Conditional movement rules promote cooperation 3 C. Athena Aktipis, John W. Pepper A General, Evolutionary Model of Long Tailed Distributions in the Social Sciences ............................................................... 13 Alexander Bentley, Paul Omerod, Michael Batty The Evolution of Institutions for Commons Management: An agent-based model ................................................................. 28 Giangiacomo Bravo Simulating “Stage” Theories: An exploration with applications ..............
    [Show full text]
  • Computational Sociology
    Emergence and social dynamics Nigel Gilbert University of Surrey [email protected] cress.soc.surrey.ac.uk Friday, April 3, 2009 1 Overview Computational social science Agent-based models Emergence in sociology Types of emergence An example The implications cress.soc.surrey.ac.uk 2 Friday, April 3, 2009 2 What is computational social science? • Models ✦ Programs as models • Mechanisms ✦ Realist accounts of the way the social world works • Experiments ✦ Experimenting on the model, as a second best to experimenting on the social world cress.soc.surrey.ac.uk 3 Friday, April 3, 2009 3 Example: Market • Many agents trading with each other • Each trying to maximise its own welfare • Neo-classical economics assumes that markets are at equilibrium, where the price is such that supply equals demand • But with a cellular automata, we can model markets in which the price varies between localities according to local supply and demand cress.soc.surrey.ac.uk 4 Friday, April 3, 2009 4 Example: Sugarscape • Agents located on a grid of cells • Trade with local neighbours • Two commodities: sugar and spice. All agents consume both these, but at different rates • Each agent has its own welfare function, relating its relative preference for sugar or spice to the amount it has ‘in stock’ and the amount it needs • Agents trade at a price negotiated between them when both would gain in welfare cress.soc.surrey.ac.uk 5 Friday, April 3, 2009 5 Example: Sugarscape cress.soc.surrey.ac.uk 6 Friday, April 3, 2009 6 Results • The expected market clearing price emerges from the many bilateral trades (but with some remaining variations) • The quantity of trade is less than that predicted by neoclassical theory ✦ since agents are unable to trade with others than their neighbours • And..
    [Show full text]
  • Petra Ahrweiler and Nigel Gilbert: Caffè Nero 10/30/2005 12:11 PM
    Petra Ahrweiler and Nigel Gilbert: Caffè Nero 10/30/2005 12:11 PM ©Copyright JASSS Petra Ahrweiler and Nigel Gilbert (2005) Caffè Nero: the Evaluation of Social Simulation Journal of Artificial Societies and Social Simulation vol. 8, no. 4 <http://jasss.soc.surrey.ac.uk/8/4/14.html> For information about citing this article, click here Received: 02-Oct-2005 Accepted: 02-Oct-2005 Published: 31-Oct-2005 Abstract This contribution deals with the assessment of the quality of a simulation by discussing and comparing "real-world" and scientific social simulations. We use the example of the Caffè Nero in Guildford as a 'real-world' simulation of a Venetian café. The construction of everyday simulations like Caffè Nero has some resemblance to the construction procedure of scientific social simulations. In both cases, we build models from a target by reducing the characteristics of the latter sufficiently for the purpose at hand; in each case, we want something from the model we cannot achieve easily from the target. After briefly discussing the 'ordinary' method of evaluating simulations called the 'standard view' and its adversary, a constructivist approach asserting that 'anything goes', we heed these similarities in the construction process and apply evaluation methods typically used for everyday simulations to scientific simulation and vice versa. The discussion shows that a 'user community view' creates the foundation for every evaluation approach: when evaluating the Caffè Nero simulation, we refer to the expert community (customers, owners) who use the simulation to get from it what they would expect to get from the target; similarly, for science, the foundation of every validity discussion is the ordinary everyday interaction that creates an area of shared meanings and expectations.
    [Show full text]
  • Developing Agent-Based Models of Complex Health Behaviour T ⁎ Jennifer Badhama, , Edmund Chattoe-Brownb, Nigel Gilbertc, Zaid Chalabid, Frank Keea, Ruth F
    Health and Place 54 (2018) 170–177 Contents lists available at ScienceDirect Health & Place journal homepage: www.elsevier.com/locate/healthplace Developing agent-based models of complex health behaviour T ⁎ Jennifer Badhama, , Edmund Chattoe-Brownb, Nigel Gilbertc, Zaid Chalabid, Frank Keea, Ruth F. Huntera a UKCRC Centre of Excellence for Public Health Research Northern Ireland, Queen's University Belfast, Institute of Clinical Sciences Block B, Royal Victoria Hospital, Belfast BT12 6BA, United Kingdom b School of Media, Communication and Sociology, University of Leicester, Bankfield House, 132 New Walk, Leicester LE1 7JA, United Kingdom c Centre for Research in Social Simulation, Department of Sociology, University of Surrey, Guildford GU 2 7XH, United Kingdom d Department of Social and Environmental Health Research, London School of Hygiene & Tropical Medicine, 15–17 Tavistock Place, London WC1H 9SH, United Kingdom ARTICLE INFO ABSTRACT Keywords: Managing non-communicable diseases requires policy makers to adopt a whole systems perspective that ade- Agent-based modelling quately represents the complex causal architecture of human behaviour. Agent-based modelling is a computa- Health behaviour tional method to understand the behaviour of complex systems by simulating the actions of entities within the Complex systems system, including the way these individuals influence and are influenced by their physical and social environ- Spatial modelling ment. The potential benefits of this method have led to several calls for greater use in public health research.We Modelling non-communicable diseases discuss three challenges facing potential modellers: model specification, obtaining required data, and developing good practices. We also present steps to assist researchers to meet these challenges and implement their agent- based model.
    [Show full text]
  • GILBERT IT and COMMUNICATIONS FBCS Freng DIRECTOR, CENTRE for RESEARCH on SIMULATION in the SOCIAL SCIENCES, UNIVERSITY of SURREY Modelling Societies
    PROFESSOR NIGEL GILBERT IT AND COMMUNICATIONS FBCS FREng DIRECTOR, CENTRE FOR RESEARCH ON SIMULATION IN THE SOCIAL SCIENCES, UNIVERSITY OF SURREY Modelling societies It is now possible to simulate on a computer the complex interactions between people, organisations and technology, and study how they evolve over time. Such ‘social simulation’ is being used to conduct experiments and test out theories that would be difficult, or impossible, to test in the real world. Nigel Gilbert explains how it all works and discusses some of the research that is currently underway. Introduction One way of exploring these issues dynamics are usually complex, that is growing in importance is to build meaning that at best only qualitative We know that collaborations between computer models that simulate the and coarse-grained predictions are universities and companies are situations in which we are interested. possible. The same applies to some important for innovation, but what kinds Researchers can then experiment with physical phenomena, such as of collaborations are most effective? the models, which is of course easier, turbulence. Nevertheless, modelling is How can the conflicting demands made quicker and involves fewer ethical and useful. It can allow one to gain a much for the water in Europe’s river basins by practical problems than experimenting deeper understanding of the factors individuals, farmers, water utilities, the with societies. that are important in a social setting, environment and transport be However, the simulations used by which policy ‘levers’ can make a reconciled? What is the most effective social scientists are fundamentally difference to outcomes and which are way of persuading farmers to manage different from most of those used in unlikely to do so.
    [Show full text]
  • OPENING PANDORA's BOX a Sociological Analysis of Scientists' Discourse G.NIGEL GILBERT Lecturer in Sociology, University of Surrey And
    OPENING PANDORA'S BOX A sociological analysis of scientists' discourse G. NIGEL GILBERT AND MICHAEL MULKAY The physicist Leo Szilard once announced to his friend Hans Bethe that he was thinking of keeping a diary: 'I don't intend to publish it; I am merely going to record the facts for the information of God.' 'Don't you think God knows the facts?' Bethe asked. 'Yes', said Szilard. 'He knows the facts, but he does not know this version of the facts.' Freeman Dyson, Disturbing the Universe (Preface) OPENING PANDORA'S BOX A Sociological analysis of scientists' discourse G.NIGEL GILBERT Lecturer in Sociology, University of Surrey and MICHAEL MULKAY Professor of Sociology, University of York Originally published by CAMBRIDGE UNIVERSITY PRESS Cambridge London New York New Rochelle Melbourne Sydney <<iv>> Published by the Press Syndicate of the University of Cambridge The Pitt Building, Trumpington Street, Cambridge CB2 1RP 32 East 57th Street, New York, NY 10022, USA 296 Beaconsfield Parade, Middle Park, Melbourne 3206, Australia © Cambridge University Press 1984 © Nigel Gilbert and Michael Mulkay 2003 First published 1984 Published on the web 2003 Originally Printed in Great Britain at the University Press, Cambridge Library of Congress catalogue card number: 83-5338 British Library Cataloguing in Publication Data Gilbert, G. Nigel Opening Pandora's Box. 1. Science-Social aspects I. Title II. Mulkay, Michael 306'.45 Q175.5 ISBN 0 521 25418 3 hard covers ISBN 0 521 27430 3 paperback <<v>> Note: the original pagination of the printed book is shown in angle brackets, thus: <<23>> Contents Acknowledgements page vi Preface vii 1 Scientists' discourse as a topic 1 2 A possible history of the field 18 3 Contexts of scientific discourse 39 4 Accounting for error 63 5 The truth will out 90 6 Constructing and deconstructing consensus 112 7 Working conceptual hallucinations 141 8 Joking apart 172 9 Pandora's bequest 188 Notes 192 Index 200 <<vi>> Acknowledgements Thanks are due to authors and publishers for permission to reproduce illustrations: from J.
    [Show full text]