Agent-Based Models and Ethnography: Combining Qualitative and Computational Techniques with Complexity Theory

2012 ◽  
Vol 35 (1) ◽  
pp. 29-33 ◽  
Author(s):  
Amanda Andrei ◽  
William Kennedy
Keyword(s):  
Complexity Theory ◽  
Cultural Practices ◽  
Computational Techniques ◽  
Agent Based Models ◽  
Social Phenomena ◽  
Agent Based ◽  
Negotiation Of Identity

Increased interaction, adaptability, diversity, and emergence are all hallmarks of complexity (Miller and Page 2007; see Simon 1996). While anthropologists may not use these specific complexity theory terms, they have long been interested in how diverse people interact and adapt in their negotiation of identity and society and what sorts of social phenomena emerge from these interactions. A complexity theory perspective can interpret culture or cultural practices as either the base rules from which identity emerges (consider Appadurai 1996) or the emergent system itself, the "webs of significance" in which humans are embedded (see Geertz 1973).

scholarly journals PROBLEMS AND PROSPECTS FOR APPLICATION OF AGENT-BASED MODELLING IN THE PSYCHOLOGY OF INFLUENCE

2021 ◽  
pp. 116-139
Author(s):  
В. В. Латынов
Keyword(s):  
Optimal Level ◽  
Psychological Research ◽  
Agent Based Modeling ◽  
Model Complexity ◽  
Agent Based Model ◽  
Agent Based Models ◽  
Social Phenomena ◽  
Agent Based ◽  
Complex Models ◽  
The Impact

В статье обсуждаются вопросы применения агент-ориентированного моделирования в психологических исследованиях. Данный вид моделирования используется для изучения систем, состоящих из большого количества взаимодействующих друг с другом агентов. Рассматривается текущее состояние и перспективы использования агентных моделей. Выделяются основные направления применения агент-ориентированного моделирования в психологии: генерирование новых и совершенствование уже существующих теорий; проверка исследовательских гипотез; построение сложных моделей социальных явлений и процессов, включающих психологические закономерности разного типа. Формулируются задачи, требующие решения при создании агентной модели: задание оптимального уровня сложности модели; достижение ее психологического реализма; выбор качеств, которыми будут обладать агенты; определение правил их взаимодействия с другими агентами и средой взаимодействия. Обсуждается проблема калибрования агентной модели, т. е. основанного на данных экспериментальных исследований обоснования необходимости введения конкретных качеств и правил взаимодействия агентов. Рассматриваются возможности агент-ориентированного моделирования при изучении процессов психологического воздействия. Выделяются теории и эмпирические закономерности, требующие учета при создании агентных моделей в области психологии воздействия. Эти теории и закономерности относятся главным образом к двум областям психологического исследования, ориентированным, соответственно, на анализ закономерностей восприятия, изменения и выражения мнений и аттитюдов на уровне отдельного индивида («двухпроцессный» подход, модель знаний о воздействии М. Фристэда и П. Райта); изучение закономерностей, связанных с влиянием на мнения, аттитюды и поведение человека его членства в группе и позиции его окружения (теория «лидеров мнения», теории групповой идентичности). The article discusses the application of agent-based modeling in psychological research. This type of modeling is used to study systems consisting of a large number of agents interacting with each other. The current state and prospects of using agent-based models are considered. The main directions of application of agent-based modeling in psychology are highlighted: generating new and improving existing theories; testing research hypotheses; construction of complex models of social phenomena and processes, including psychological patterns of various types. The tasks that need to be solved when creating an agent-based model are formulated: setting the optimal level of model complexity; achieving her psychological realism; choice of qualities that agents will possess; defining the rules for their interaction with other agents and the interaction environment. The problem of calibrating the agent-based model is discussed, that is, substantiating the need to introduce specific qualities and rules for the interaction of agents based on experimental research data. The possibilities of agent-based modeling in the study of the processes of psychological influence are considered. Theories and empirical patterns are highlighted that require consideration when creating agent-based models in the field psychology of influence. These theories and patterns relate mainly to two areas of psychological research, focused, respectively, on the analysis of patterns of perception, change and expression of opinions and attitudes at the level of an individual ("two-process" approach, the model of knowledge about the impact of M. Freestad and P. Wright); study of the patterns associated with the influence on the opinions, attitudes and behavior of a person by his membership in a group and the position of his environment (theory of "opinion leaders", theories of group identity).

A case for agent-based models in organizational behavior and team research

2015 ◽  
Vol 21 (1/2) ◽  
pp. 37-50 ◽  
Author(s):  
Davide Secchi
Keyword(s):  
Organizational Behavior ◽  
Design Methodology ◽  
Agent Based Models ◽  
Social Phenomena ◽  
Content Type ◽  
Agent Based ◽  
The Past ◽  
Team Research ◽  
Software Platforms ◽  
User Friendly

Purpose – This paper aims at introducing agent-based models (ABMs) and reviews some of their features in an attempt to show why they can be useful for organizational behavior research. Design/methodology/approach – The use of simulations has increased substantially in the past ten to fifteen years, but management seems to hold back to the agent-based “revolution”. The paper first describes the ABMs, and then discusses some of the issues that usually prevent management scholars from using simulations. Findings – This paper indicates how an agent-based approach can help overcome the hesitations surrounding computer simulations because (a) it makes it relatively easy to model emergent and complex social phenomena, and (b) simulation is made easier by user-friendly software platforms that connect it to the existing research methods. Originality/value – This article describes ABMs in a way that may be attractive to organization scholars, and it depicts the frontiers of a more flexible computational and mathematical approach to organizations, management and teams.

scholarly journals Building Better Ecological Machines: Complexity Theory and Alternative Economic Models

2016 ◽  
Vol 2 ◽  
pp. 266
Author(s):  
Jess Bier ◽  
Willem Schinkel
Keyword(s):  
Economic Crisis ◽  
Complexity Theory ◽  
Economic Models ◽  
Financial Policy ◽  
Agent Based Models ◽  
Agent Based ◽  
Macroeconomic Models ◽  
Fractal Modeling ◽  
Current Economic Crisis ◽  
Conventional Models

Computer models of the economy are regularly used to predict economic phenomena and set financial policy. However, the conventional macroeconomic models are currently being reimagined after they failed to foresee the current economic crisis, the outlines of which began to be understood only in 2007-2008. In this article we analyze the most prominent of this reimagining: Agent-Based models (ABMs). ABMs are an influential alternative to standard economic models, and they are one focus of complexity theory, a discipline that is a more open successor to the conventional chaos and fractal modeling of the 1990s. The modelers who create ABMs claim that their models depict markets as ecologies, and that they are more responsive than conventional models that depict markets as machines. We challenge this presentation, arguing instead that recent modeling efforts amount to the creation of models as ecological machines. Our paper aims to contribute to an understanding of the organizing metaphors of macroeconomic models, which we argue is relevant conceptually and politically, e.g., when models are used for regulatory purposes.

Computational Methods for Socio-Computer Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Mingkun Gao ◽  
Hyo Jin Do
Keyword(s):  
Computational Methods ◽  
User Interfaces ◽  
Social Processes ◽  
Computational Techniques ◽  
Special Focus ◽  
Design Features ◽  
Social Phenomena ◽  
Online Social Media ◽  
Social Opinions ◽  
Computer Interaction

From the Arab Spring to presidential elections, various forms of online social media, forums, and networking platforms have been playing increasing significant roles in our societies. These emerging socio-computer interactions demand new methods of understanding how various design features of online tools may moderate the percolation of information and gradually shape social opinions, influence social choices, and moderate collective action. This chapter starts with a review of the literature on the different ways technologies impact social phenomena, with a special focus on theories that characterize how social processes are moderated by various design features of user interfaces. It then reviews different theory-based computational methods derived from these theories to study socio-computer interaction at various levels. Specific examples of computational techniques are reviewed to illustrate how they can be useful for influencing social processes for various purposes. The chapter ends with how future technologies should be designed to improve socio-computer interaction.

scholarly journals Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  
Keyword(s):  
Species Interactions ◽  
Computational Models ◽  
Human Microbiome ◽  
Agent Based Modeling ◽  
Autonomous Agent ◽  
Agent Based Models ◽  
Agent Based ◽  
Complex Interactions ◽  
Mucosal Surfaces ◽  
Living Organisms

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.

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