No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Design Research through simulated social complexity. An agent-based proposal to the construction of design knowledge
... Maria highlights that when selecting an appropriate experimental design, several factors needed to be identified: a performance measure needs to be identified, input variables that influence the performance measure need to be selected along with the degree of each input variable, and the experimental design needs to be documented [14]. Based on this measure, many agent-based models for simulation in engineering design reviewed in the literature survey present an experimental design, but few publications thoroughly document the selected experimental design used and provide justification [7,15,16,18,[21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. To address this gap, a more systematic approach to experimental design needs to be taken. ...
Agent-based modeling (ABM) is a widely used simulation methodology. The use of ABM in engineering design continues to grow due to increasing interest in modeling and simulating human systems. However, there are few resources specific to engineering design that guide how to develop an ABM, execute an ABM experiment, and assess the subsequent results. This inhibits the effective use of ABM by design researchers who are new to the methodology. The goal of this paper is to provide a resource for both novice and experienced design researchers that details a systematic approach to ABM. First, this paper reviews current ABM research in engineering design, with a specific focus on models used to simulate human systems. Specifically, we review this work with respect to a step-by-step approach to modeling developed in the systems simulation literature. Second, each of the steps is contextualized with respect to the literature review, identifying heuristics and best practices. Through this contextualization, gaps in current practice are also identified.
Design is everywhere. It influences how we live, what we wear, how we communicate, what we buy, and how we behave. To design for the real world and define strategies rather than just implement them, you need to learn how to understand and solve complex, intricate and often unexpected problems. Research for Designers is the guide to this new, evidence-based creative process for anyone doing research in Design Studies or looking to develop their design research skills.
The book takes an organized approach to walking you through the basics of research, highlights the importance of data, and encourages you to think in a cross-disciplinary way.
Including interviews with 10 design experts from across the globe, this guide helps you put theory into practice and conduct successful design research.
The book also features a Foreword by Ken Friedman, a new Preface with Don Norman, and an Afterword by Steven Heller.
This paper introduces a mixed-method research design for investigating complexity of social reality. The research design integrates grounded theory (Glaser and Strauss, 1967) and social simulation and is therefore called grounded simulation (GS). GS starts with in-depth investigations of complex social phenomena from perspectives of people who experience them. These investigations follow principles of grounded theory and enquire into contexts that research participants describe and the way they make sense of action in these contexts. Data analysis progresses inductively and outwards, from narratives of people who are at the centre of the phenomena to emerging constructs and theories. While the grounded theory fieldwork would have its own research outputs, its selected findings can be then carried to agent-based models for further investigation of social complexity. By representing social and economic agents, their contexts and actions as closely as possible, GS shortens the distance between research participants, who have real life experiences of the subject being modelled, and the virtual agents. Knowledge production in social simulation progresses generatively and upwards, moving from interactions at the individual level to emergent properties at the macro-level. GS experiments are thus suitable for studying the societal implications of meanings that emerge from the data collected in grounded theory. The paper illustrates how this research design can be used, by referring to a GS study on diffusion of innovations.
Outlining state-of-the-art developments in the area of complexity and design, this book collates them into a unique and authoritative resource for both the design and complex systems communities. The book is based on research which focuses on a variety of different themes and domains, including architecture, engineering, environmental design, art, fashion and management. A ground-breaking publication marking a new era of appreciation of the import of complexity on design, this book is essential reading for those studying complexity or design.
In social science, the role of stakeholders is increasing in the development and use of simulation models. Their participation in the design of agent-based models (ABMs) has widely been considered as an efficient solution to the validation of this particular type of model. Traditionally, "agents" (as basic model elements) have not been concerned with stakeholders directly but via designers or role-playing games (RPGs). In this paper, we intend to bridge this gap by introducing computational or software agents, implemented from an initial ABM, into a new kind of RPG, mediated by computers, so that these agents can interact with stakeholders. This interaction can help not only to elicit stakeholders' informal knowledge or unpredicted behaviours, but also to control stakeholders' focus during the games. We therefore formalize a general participatory design method using software agents, and illustrate it by describing our experience in a project aimed at developing agent-based social simulations in the field of air traffic management.
In 2001, Olivier Barreteau proposed to jointly use multi-agent systems and role-playing games for purposes of research, training and negotiation support in the field of renewable resource management. This joint use was later labeled the "MAS/RPG methodology" and this approach is one of the foundation stones of the ComMod movement. In this article, we present an alternative method called "agent-based participatory simulations". These simulations are multi-agent systems where human participants control some of the agents. The experiments we conducted prove that it is possible to successfully merge multi-agent systems and role-playing games. We argue that agent-based participatory simulations are also a significant improvement over the MAS/RPG approach, opening new perspectives and solving some of the problems generated by the joint use of role-playing games and multi-agent systems. The advantages are at least threefold. Because all interactions are computer mediated, they can be recorded and this record can be processed and used to improve the understanding of participants and organizers alike. Because of the merge, agent-based participatory simulations decrease the distance between the agent-based model and the behavior of participants. Agent-based participatory simulations allow for computer-based improvements such as the introduction of eliciting assistant agents with learning capabilities.
page 14 Declaration - page 15 Notes of copyright and the ownership of intellectual property rights - page 15 The Author - page 16 Acknowledgements - page 16 1 - Introduction - page 17 1.1 - Background - page 17 1.2 - The Style of Approach - page 18 1.3 - Motivation - page 19 1.4 - Style of Presentation - page 20 1.5 - Outline of the Thesis - page 21 2 - Models and Modelling - page 23 2.1 - Some Types of Models - page 25 2.2 - Combinations of Models - page 28 2.3 - Parts of the Modelling Apparatus - page 33 2.4 - Models in Machine Learning - page 38 2.5 - The Philosophical Background to the Rest of this Thesis - page 41 Syntactic Measures of Complexity - page 3 - 3 - Problems and Properties - page 44 3.1 - Examples of Common Usage - page 44 3.1.1 - A case of nails - page 44 3.1.2 - Writing a thesis - page 44 3.1.3 - Mathematics - page 44 3.1.4 - A gas - page 44 3.1.5 - An ant hill - page 45 3.1.6 - A car engine - page 45 3.1.7 - A cell as part of an organism -...
The initiatives of cycling infrastructure enhancements around the world reveal a consistent interest in promoting cycling to transition toward sustainable lifestyles and safe multi-modal commuting. Accordingly, proposals for cyber-physical systems for smart cycling are also growing, providing solutions to make cycling a safer and better experience for cyclists. However, most existent solutions address single cyclist problems rather than group cycling issues. It is evident that further work is needed to improve safety and comfort for groups of cyclists traveling on busy urban bicycle paths or dedicated bicycle highways. In this paper, we position the concept of technology-assisted cooperative cycling. We introduce a platoon-based cyclist cooperative system that provides safe and efficient coordination for groups of cyclists. We present the results of an experimental prototype tested on real cyclists as well as comprehensive simulations that test the performance of our solution in different scenarios. We demonstrate that our system is feasible to implement and tolerates the human error factor while it is still able to achieve a constant spacing policy. Coordinated platoons of bicycles can be extremely useful to maximize the positive impact of green waves of traffic lights for cyclists and can be extended to groups of two-wheeled vehicles, including mopeds and self-balanced electric vehicles.
This volume examines all aspects of using agent or individual-based simulation. This approach represents systems as individual elements having their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes this "social" is that it can represent an observed society.
Social systems include all those systems where the components have individual agency but also interact with each other. This includes human societies and groups, but also increasingly socio-technical systems where the internet-based devices form the substrate for interaction. These systems are central to our lives, but are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible but, on the other hand, natural language approaches are also inadequate for relating intricate cause and effect. This is why individual an
d agent-based computational approaches hold out the possibility of new and deeper understanding of such systems.
This handbook marks the maturation of this new field. It brings together summaries of the best thinking and practices in this area from leading researchers in the field and constitutes a reference point for standards against which future methodological advances can be judged.
This second edition adds new chapters on different modelling purposes and applying software engineering methods to simulation development. Revised existing content will keep the book up-to-date with recent developments. This volume will help those new to the field avoid "reinventing the wheel" each time, and give them a solid and wide grounding in the essential issues. It will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introduction, Methodology, Mechanisms, and Applications
. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section on ‘Further Reading’.
Whilst sometimes covering technical aspects, this second edition of Simulating Social Complexity is designed to be accessible to a wide range of researchers, including both those from the social sciences as well as those with a more formal background. It will be of use as a standard reference text in the field and also be suitable for graduate level courses.
Over twenty years ago, when I began the research that illustrates the methods advocated in this chapter, the theoretical issues about the nature of culture that I intended this research to address were very much unsettled. An older theory of linguistic meaning, on which the theory of cultural meaning that I had learned in graduate school had been predicated, was failing. It was up to my generation of cognitive anthropologists, I felt, to build a new and better theory of culture. An exciting new framework, that held promise for cognitive anthropology, was emerging from the multidisciplinary enterprise of cognitive science. But the ideas we were borrowing from cognitive science were themselves still young, undeveloped, and disputed.
Computational modeling is a powerful method for building theory. However, to construct a computational model, researchers need to operationalize their cognitive or verbal theory into the specific terms demanded by the simulation’s language. This requires the researcher to make a series of reasonable assumptions to fill unanticipated “specificity gaps.” The problem is that many other reasonable assumptions could also have been made, and many of those resulting models would also match the conceptual theory. This is the problem of equifinality. We demonstrate the power and the dangers of computational modeling by building a simulation of a classic small group study. The results demonstrate that reasonable assumptions and equifinality are straightforward (but often overlooked) problems at the core of genuinely useful methodology. We offer recommendations and hope to open a dialog on other perspectives and solutions.
Sociologists have long believed that psychology alone can't explain what happens when people work together in complex modern societies. In contrast, most psychologists and economists believe that we can explain much about social life with an accurate theory of how individuals make choices and act on them. R. Keith Sawyer argues, however, that societies are complex dynamical systems, and that the best way to resolve these debates is by developing the concept of emergence, paying attention to multiple levels of analysis--individuals, interactions, and groups--with a dynamic focus on how social group phenomena emerge from communication processes among individual members.
It has been argued by Per Galle that a viable account of designing should address the ‘problem of the absent artifact’. The problem concerns the nature of design representations. Specifically, the question how one can utter true statements, in terms of design representations, about artifacts when these artifacts are, in the design phase, still non-existent. This paper exposes the problem as a pseudo-problem. It is argued that design representations are not means for the production of truth-apt assertions. This dissolves the ‘absent artifact problem’. An alternative view is elaborated according to which design representations are means for counterfactual understanding, knowledge generalisation, and knowledge unification. Examples from the functional modelling literature are used to illustrate these roles.
The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.
Design thinking is the core creative process for any designer; this book explores and explains this apparently mysterious “design ability.”
Focusing on what designers do when they design, Design Thinking is structured around a series of in-depth case studies of outstanding and expert designers, interwoven with overviews and analyses. The range covered reflects the breadth of design, from hardware and software design to architecture and Formula One. The book offers new insights into and understanding of design thinking, based on evidence from observation and investigation of design practice.
Design Thinking is the distillation of the work of one of design’s most influential scholars. Nigel Cross goes to the heart of what it means to think and work as a designer. The book is an ideal guide for anyone who wants to be a designer or to know how good designers work in the field of contemporary design.
Proposes a model of social systems based on general systems research, cybernetics, and information and communication theory. Contains reviews and critiques of important sociological approaches. Harvard Book List (edited) 1971 #677 (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Can computers change what you think and do? Can they motivate you to stop smoking, persuade you to buy insurance, or convince you to join the Army? "Yes, they can," says Dr. B.J. Fogg, director of the Persuasive Technology Lab at Stanford University. Fogg has coined the phrase "Captology"(an acronym for computers as persuasive technologies) to capture the domain of research, design, and applications of persuasive computers.In this thought-provoking book, based on nine years of research in captology, Dr. Fogg reveals how Web sites, software applications, and mobile devices can be used to change peoples attitudes and behavior. Technology designers, marketers, researchers, consumers-anyone who wants to leverage or simply understand the persuasive power of interactive technology-will appreciate the compelling insights and illuminating examples found inside. Persuasive technology can be controversial-and it should be. Who will wield this power of digital influence? And to what end? Now is the time to survey the issues and explore the principles of persuasive technology, and B.J. Fogg has written this book to be your guide.
This paper introduces Niklas Luhmann's final work, Die Gesellschaft der Gesellschaft (The Society of Society). According to Luhmann, sociologists have failed to produce even a partially adequate theory of society. Epistemological obstacles and humanist concerns for rationality and justice have prevented true progress in the discipline. With his “radically antihumanist, radically antiregional, and radically constructivistic” social system theory, Luhmann intends to bring about a sociological enlightenment. Die Gesellschaft der Gesellschaft focuses on communication as the only genuinely social phenomenon. Social systems differentiate and evolve as they communicate in three separate dimensions: the social, temporal, and functional. The path of evolution results from a history of variation, selection, and restabilization within these dimensions. Communication, bit by bit, produces social structures that, recursively, produce future structures. Society is communication. Sociology, as the science of society, is communication about how different societal systems operate, communicate, evolve, and maintain their boundaries.
The search for scientific bases for confronting problems of social policy is bound to fail, becuase of the nature of these problems. They are wicked problems, whereas science has developed to deal with tame problems. Policy problems cannot be definitively described. Moreover, in a pluralistic society there is nothing like the undisputable public good; there is no objective definition of equity; policies that respond to social problems cannot be meaningfully correct or false; and it makes no sense to talk about optimal solutions to social problems unless severe qualifications are imposed first. Even worse, there are no solutions in the sense of definitive and objective answers.
Anticipation indicates the capacity to act in preparation for a certain effect or future state of the world. Although the link between anticipation and design has not received particular attention in design research, it is a fundamental one. In the paper we review the concept of anticipation and discuss its meaning for design research. We further argue that in order to develop an anticipatory view of design it is necessary to move beyond long-established paradigms and abstractions such as those of machine, evolution and control. Based on a conceptual and methodological framework proposed by Robert Rosen we elaborate such an anticipatory view that establishes the uniqueness of design compared to these paradigms.
How can machines support or, even more significantly, replace humans in performing ethical reasoning? This question greatly interests machine ethics researchers. Imbuing a computer with the ability to reason about ethical problems and dilemmas is as difficult a task as there is for AI scientists and engineers. The author briefly describes a few of the programs and discusses in detail two programs, both of which employ techniques from the area of AI known as case-based reasoning and implement aspects of the ethical approach known as casuistry. One of these programs, Truth-Teller, accepts a pair of ethical dilemmas and describes the salient similarities and differences between them, from both an ethical and a pragmatic perspective. The other program, SIROCCO, accepts a single ethical dilemma and retrieves other cases and ethical principles that might be relevant
This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.
How do social structures and group behaviors arise from the interaction of individuals? Growing Artificial Societies approaches this question with cutting-edge computer simulation techniques. Fundamental collective behaviors such as group formation, cultural transmission, combat, and trade are seen to "emerge" from the interaction of individual agents following a few simple rules. In their program, named Sugarscape, Epstein and Axtell begin the development of a "bottom up" social science that is capturing the attention of researchers and commentators alike. The study is part of the 2050 Project, a joint venture of the Santa Fe Institute, the World Resources Institute, and the Brookings Institution. The project is an international effort to identify conditions for a sustainable global system in the next century and to design policies to help achieve such a system.
It is becoming widely accepted that applied social simulation research is more effective if potential users and stakeholders are closely involved in model specification, design, testing and use, using the principles of participatory research. In this paper, a review of software engineering principles and accounts of the development of simulation models are used as the basis for recommendations about some useful techniques that can aid in the development of agent-based social simulation models in conjunction with users. The authors' experience with scenario analysis, joint analysis of design workshops, prototyping and user panels in a collaborative participatory project is described and, in combination with reviews from other participatory projects, is used to suggest how these techniques might be used in simulation-based research.
Agent-based approaches are becoming increasingly important because
of their generality, flexibility, modularity, and ability to take
advantage of distributed resources. Agents are used in information
retrieval, entertainment, coordinating multiple robots, and modeling
economic systems. Agents can recommend music, tell stories, and interact
with people. They are useful for reducing humans' work and information
load in tasks such as medical monitoring and battlefield reasoning.
Agents are already changing the way in which we gather information,
manage investments, and conduct business. This article provides an
introduction to agent issues, outlines motivations for using agent-based
paradigms, and describes some of their current uses
The complex loop of norm emergence: A simulation model
- G Andrighetto
- M Campennì
- F Cecconi
- R Conte
Andrighetto, G., Campennì, M., Cecconi, F., and Conte, R. (2010). The complex loop of norm
emergence: A simulation model. In Takadama, K., Cioffi-Revilla, C., and Deffuant, G., editors,
Simulating Interacting Agents and Social Phenomena: The Second World Congress, page 280 p.
Springer Science & Business Media, Tokio, Japan.
Motivation, capacity, and opportunity as related to the use of casework service: Theoretical base and plan of study
- R D'andrade
D'Andrade, R. (1995). Motivation, capacity, and opportunity as related to the use of casework
service: Theoretical base and plan of study. Current Anthropology, 36(3):399-408.
The Nature of Design Thinking
- K Dorst
Dorst, K. (2010). The Nature of Design Thinking. In DTRS8 Interpreting Design Thinking: Design
Thinking Research Symposium Proceedings, pages 131 -139.
Varieties of emergence
- N Gilbert
Gilbert, N. (2002). Varieties of emergence. In Edited transcript of the introductory talk given at the
workshop on Agent 2002 Social Agents: Ecology, Exchange, and Evolution Conference.
Using complexity science framework and multi-agent technology in design
- G Rzevski
Rzevski, G. (2010). Using complexity science framework and multi-agent technology in design. In
Alexiou, K., Johnson, J., and Zamenopoulos, T., editors, Embracing complexity in design, pages 61-72. Routledge, Abingdon, OX.
Simulating social complexity: a handbook
- K G Troitzsch
Troitzsch, K. G. (2013). Historical introduction. In Edmonds, Bruce, M. R., editor, Simulating social
complexity: a handbook. Springer, New York.
Kritische theorie der formbildung. Gebrüder Borntraeger
- L Von Bertalanffy
von Bertalanffy, L. (1928). Kritische theorie der formbildung. Gebrüder Borntraeger, Berlin.
von Bertalanffy, L. (1972). The history and status of general systems theory. Academy of
Management Journal, 15(4):407-426.
Netlogo disease solo model
- U Wilensky
Wilensky, U. (2005). Netlogo disease solo model. Center for Connected Learning and Computer-Based
Modeling. Northwestern University, Evanston, IL.