scholarly journals Anticipation and the Dynamics of Expectations

2021 ◽  
pp. 149-173
Author(s):  
Loet Leydesdorff
Keyword(s):  
Discourse Analysis ◽  
Scientific Knowledge ◽  
Agent Based ◽  
Individual Level ◽  
Sociology Of Scientific Knowledge ◽  
Historical Dynamics ◽  
The Status ◽  
The Individual ◽  
Anticipatory Systems ◽  
Recursive Dynamics

AbstractThe operationalization of socio-cognitive structures in terms of observables such as texts (e.g., in discourse analysis and scientometrics) or the behavior of agents (e.g., in the sociology of scientific knowledge) may inadvertedly lead to reification. The dynamics of knowledge are not directly observable, but knowledge contents can be reconstructed. The reconstructions have the status of hypotheses; hypotheses can be tested against observations. Whereas agent-based modelling (ABM) focuses on observable behavior, simulations based on algorithms developed in the theory and computation of anticipatory systems (CASYS) enable us to visualize the incursive and recursive dynamics of knowledge at the individual level as different from the potentially hyper-incursive dynamics at the intersubjective level. The sciences can be considered as “strongly anticipatory” at this supra-individual level: expectations are discursively reconstructed in terms of next generations of expectations. This reflexive restructuring is embedded in historical dynamics on which it feeds back as a selection environment. The agents and texts entertain discursive models and thus be considered “weakly anticipatory” participants in the communication.

scholarly journals Collective patterns of social diffusion are shaped by individual inertia and trend-seeking

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mengbin Ye ◽  
Lorenzo Zino ◽  
Žan Mlakar ◽  
Jan Willem Bolderdijk ◽  
Hans Risselada ◽  
...  
Keyword(s):  
Population Level ◽  
Agent Based ◽  
Individual Level ◽  
Social Conventions ◽  
The Social ◽  
The Status ◽  
Diffusion Pattern ◽  
Social Diffusion ◽  
Psychology Literature ◽  
The Individual

AbstractSocial conventions change when individuals collectively adopt an alternative over the status quo, in a process known as social diffusion. Our repeated trials of a multi-round experiment provided data that helped motivate the proposal of an agent-based model of social diffusion that incorporates inertia and trend-seeking, two behavioural mechanisms that are well documented in the social psychology literature. The former causes people to stick with their current decision, the latter creates sensitivity to population-level changes. We show that such inclusion resolves the contradictions of existing models, allowing to reproduce patterns of social diffusion which are consistent with our data and existing empirical observations at both the individual and population level. The model reveals how the emergent population-level diffusion pattern is critically shaped by the two individual-level mechanisms; trend-seeking guarantees the diffusion is explosive after the diffusion process takes off, but inertia can greatly delay the time to take-off.

Simulating an Incentive Framework for Scientific Production by Means of Adaptive Agents

2014 ◽  
pp. 221-238
Author(s):  
Gabriel Franklin ◽  
Tibérius O. Bonates
Keyword(s):  
Incentive Mechanism ◽  
Scientific Production ◽  
Agent Based Simulation ◽  
Adaptive Agents ◽  
Scientific Publications ◽  
Agent Based ◽  
Individual Level ◽  
Original Target ◽  
Negative Effect ◽  
The Individual

This chapter describes an agent-based simulation of an incentive mechanism for scientific production. In the proposed framework, a central agency is responsible for devising and enforcing a policy consisting of performance-based incentives in an attempt to induce a global positive behavior of a group of researchers, in terms of number and type of scientific publications. The macro-level incentive mechanism triggers micro-level actions that, once intensified by social interactions, lead to certain patterns of behavior from individual agents (researchers). Positive reinforcement from receiving incentives (as well as negative reinforcement from not receiving them) shape the behavior of agents in the course of the simulation. The authors show, by means of computational experiments, that a policy devised to act at the individual level might induce a single global behavior that can, depending on the values of certain parameters, be distinct from the original target and have an overall negative effect. The agent-based simulation provides an objective way of assessing the quantitative effect that different policies might induce on the behavior of individual researchers when it comes to their preferences regarding scientific publications.

Macroscopic Modeling of Information Flow in an Agent-Based Electronic Health Record System

2011 ◽  
pp. 305-334
Author(s):  
Ben Tse
Keyword(s):  
Electronic Health Record ◽  
Electronic Health Record System ◽  
Health Record ◽  
Record System ◽  
Macroscopic Modeling ◽  
Agent Based ◽  
Individual Level ◽  
Patient Health ◽  
Electronic Health ◽  
The Individual

This chapter presents an architecture, or general framework, for an agent-based electronic health record system (ABEHRS) to provide health information access and retrieval among different medical services facilities. The agent system’s behaviors are analyzed using the simulation approach and the mathematical modeling approach. The key concept promoted by ABEHRS is to allow patient health records to autonomously move through the computer network uniting scattered and distributed data into one consistent and complete data set or patient health record. ABEHRS is an example of multi-agent swarm system, which is composed of many simple agents and a system that is able to self-organize. The ultimate goal is that the reader should appreciate the benefits of using mobile agents and the importance of studying agent behaviors at the system level and at the individual level.

Dynamic Capabilities and Where to Find Them

2017 ◽  
Vol 29 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Seidali Kurtmollaiev
Keyword(s):  
Dynamic Capabilities ◽  
Sufficient Conditions ◽  
Resource Base ◽  
Firm Level ◽  
Individual Level ◽  
The Status ◽  
The Individual ◽  
High Level ◽  
Necessary And Sufficient ◽  
Intention To Change

Despite its immense popularity, the dynamic capabilities framework faces fierce criticism because of the ambiguous and contradictory interpretations of dynamic capabilities. Especially challenging are the aspects related to the nature of dynamic capabilities and the issue of agency. In an attempt to avoid circular and overlapping definitions, I explicate dynamic capabilities as the regular actions of creating, extending, and modifying an organizational resource base. This implies that the individual’s intention to change the status quo in the organization and the individual’s high level of influence in the organization are necessary and sufficient conditions for dynamic capabilities. This approach overcomes challenges associated with current interpretations of dynamic capabilities, necessarily focusing on the actions and interactions of individuals in organizations. Following the micro-foundations movement, I present a multilevel approach for studying the individual-level causes and the firm-level effects of dynamic capabilities.

ANALYZING THE AGENT-BASED MODEL AND ITS IMPLICATIONS

2003 ◽  
Vol 06 (03) ◽  
pp. 331-347 ◽  
Author(s):  
YUTAKA I. LEON SUEMATSU ◽  
KEIKI TAKADAMA ◽  
NORBERTO E. NAWA ◽  
KATSUNORI SHIMOHARA ◽  
OSAMU KATAI
Keyword(s):  
Social Sciences ◽  
Internal Structure ◽  
Design Methodology ◽  
Social Systems ◽  
Agent Based Model ◽  
Social Phenomena ◽  
Agent Based ◽  
Individual Level ◽  
The Social ◽  
The Individual

Agent-based models (ABMs) have been attracting the attention of researchers in the social sciences, becoming a prominent paradigm in the study of complex social systems. Although a great number of models have been proposed for studying a variety of social phenomena, no general agent design methodology is available. Moreover, it is difficult to validate the accuracy of these models. For this reason, we believe that some guidelines for ABMs design must be devised; therefore, this paper is a first attempt to analyze the levels of ABMs, identify and classify several aspects that should be considered when designing ABMs. Through our analysis, the following implications have been found: (1) there are two levels in designing ABMs: the individual level, related to the design of the agents' internal structure, and the collective level, which concerns the design of the agent society or macro-dynamics of the model; and (2) the mechanisms of these levels strongly affect the outcomes of the models.

A CONNECTIONIST ABM OF SOCIAL CATEGORIZATION PROCESSES

2012 ◽  
Vol 15 (06) ◽  
pp. 1250077 ◽  
Author(s):  
DIRK VAN ROOY
Keyword(s):  
Social Influence ◽  
Network Structure ◽  
Social Adaptation ◽  
Multiple Sources ◽  
Agent Based ◽  
Individual Level ◽  
Extensive Research Program ◽  
Micro Level ◽  
The Individual ◽  
Over Time

This paper introduces a connectionist Agent-Based Model (cABM) that incorporates detailed, micro-level understanding of social influence processes derived from laboratory studies and that aims to contextualize these processes in such a way that it becomes possible to model multidirectional, dynamic influences in extended social networks. At the micro-level, agent processes are simulated by recurrent auto-associative networks, an architecture that has a proven ability to simulate a variety of individual psychological and memory processes [D. Van Rooy, F. Van Overwalle, T. Vanhoomissen, C. Labiouse and R. French, Psychol. Rev. 110, 536 (2003)]. At the macro-level, these individual networks are combined into a "community of networks" so that they can exchange their individual information with each other by transmitting information on the same concepts from one net to another. This essentially creates a network structure that reflects a social system in which (a collection of) nodes represent individual agents and the links between agents the mutual social influences that connect them [B. Hazlehurst, and E. Hutchins, Lang. Cogn. Process. 13, 373 (1998)]. The network structure itself is dynamic and shaped by the interactions between the individual agents through simple processes of social adaptation. Through simulations, the cABM generates a number of novel predictions that broadly address three main issues: (1) the consequences of the interaction between multiple sources and targets of social influence (2) the dynamic development of social influence over time and (3) collective and individual opinion trajectories over time. Some of the predictions regarding individual level processes have been tested and confirmed in laboratory experiments. In a extensive research program, data is currently being collected from real groups that will allow validating the predictions of cABM regarding aggregate outcomes.

scholarly journals A HYBRID MODEL FOR STUDYING SPATIAL ASPECTS OF INFECTIOUS DISEASES

2012 ◽  
Vol 54 (1-2) ◽  
pp. 37-49 ◽  
Author(s):  
BENJAMIN J. BINDER ◽  
JOSHUA V. ROSS ◽  
MATTHEW J. SIMPSON
Keyword(s):  
Infectious Disease ◽  
Spatial Analysis ◽  
Infectious Diseases ◽  
Hybrid Model ◽  
Population Level ◽  
Infectious Agents ◽  
Agent Based ◽  
Individual Level ◽  
The Individual ◽  
Spread Of Infection

AbstractWe consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

Macroscopic Modeling of Information Flow in an Agent-Based Electronic Health Record System

2011 ◽  
pp. 602-630
Author(s):  
Ben Tse
Keyword(s):  
Electronic Health Record ◽  
Electronic Health Record System ◽  
Health Record ◽  
Record System ◽  
Macroscopic Modeling ◽  
Agent Based ◽  
Individual Level ◽  
Patient Health ◽  
Electronic Health ◽  
The Individual

This chapter presents an architecture, or general framework, for an agent-based electronic health record system (ABEHRS) to provide health information access and retrieval among different medical services facilities. The agent system’s behaviors are analyzed using the simulation approach and the mathematical modeling approach. The key concept promoted by ABEHRS is to allow patient health records to autonomously move through the computer network uniting scattered and distributed data into one consistent and complete data set or patient health record. ABEHRS is an example of multi-agent swarm system, which is composed of many simple agents and a system that is able to self-organize. The ultimate goal is that the reader should appreciate the benefits of using mobile agents and the importance of studying agent behaviors at the system level and at the individual level.

scholarly journals Status Construction During COVID-19: Antibody Positive People's Rising Prestige

2020 ◽  
Vol 5 ◽  
Author(s):  
M. D. R. Evans ◽  
Jonathan Kelley ◽  
Sarah Kelley
Keyword(s):  
State Theory ◽  
Cultural Value ◽  
Individual Level ◽  
Social Scripts ◽  
General Logic ◽  
The Status ◽  
The Individual ◽  
Small Elements ◽  
New Inequalities ◽  
Do So

The protracted COVID-19 crisis provides a new social niche in which new inequalities can emerge. We provide predictions about one such new inequality using the logic of Status Construction Theory (SCT). SCT, rooted in Expectations State Theory and from there developed by Ridgeway and colleagues, proposes general hypotheses about how new inequalities arise through process of interaction at the individual level: an unordered categorical difference becomes attached to a cultural value that gives one category more value than the other; social scripts concerning it emerge; small elements of assertion and deference creep into more and more encounters that an individual participates in, hears about through networks, and learns about via social and conventional media. The categorical difference begins to morph into a hierarchical status distinction. Through these mechanisms, individuals develop “status beliefs” that most people in their communities endorse the status distinction. Although they may or may not endorse the distinction personally, they believe that most people do so and they find that the path of least resistance socially is to enact the scripts that affirm the higher status/prestige of the favored group. We apply Status Construction Theory to the categorical difference between Antibody Positives (who have been tested for IgG antibodies) and Others (everybody else). Using the general logic of SCT and specifically developing applications of its key propositions, we predict that the categorical difference between Antibody Positives and Others will transition to a status distinction and propose testable, falsifiable hypotheses about each step of the process.

scholarly journals Reduced Meat Consumption: from Multicriteria Argument Modelling to Agent-Based Social Simulation

2021 ◽  
Vol 10 (1) ◽  
pp. 133-149
Author(s):  
Rallou Thomopoulos ◽  
Nicolas Salliou ◽  
Carolina Abreu ◽  
Vincent Cohen ◽  
Timothée Fouqueray
Keyword(s):  
Nutrition Transition ◽  
Meat Consumption ◽  
Developed Countries ◽  
Individual Values ◽  
Animal Products ◽  
Agent Based ◽  
Individual Level ◽  
Vegetarian Diets ◽  
The Individual ◽  
The Impact

A second nutrition transition seems to be emerging towards more plant-based diets, curbing meat consumption in developed countries at the beginning of the 21st century. This shift suggests that rational arguments tend to influence an increasing number of individuals to adopt vegetarian diets. This work aimed to understand and simulate the impact of different types of messages on the choice to change food diets at the individual level, and the impact of the diffusion of opinions at the collective level. It provided two results: (1) a network of arguments around vegetarian diets is modelled using an abstract argumentation approach. Each argument, formalized by a node, was connected with other arguments by arrows, thus formalizing relationships between arguments. This methodology made it possible to formalize an argument network about vegetarian diets and to identify the importance of health arguments compared to ethical or other types of arguments. This methodology also identified key arguments as a result of their high centrality in being challenged or challenging other arguments. The results of constructing this argument network suggested that any controversy surrounding vegetarian diets will be polarized around such high centrality arguments about health. Even though few ethical arguments appeared in our network, the health arguments concerning the necessity or not of animal products for humans were indirectly connected with ethical choices towards vegetarian diets; (2) an agent-based simulation of the social diffusion of opinions and practices concerning meat consumption is then introduced. The purpose of this simulation was to capture the balance of vegetarian vs. meat-based diets. It contributes to modelling consumer choices by exploring the balance between individual values and external influences such as social pressure, communication campaigns and sanitary, environmental or ethical crises.

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