scholarly journals Multiscale Modeling of Social Systems: Scale Bridging via Decision Making

2019 ◽  
pp. 617-624
Author(s):  
Nursultan Nikhanbayev ◽  
Toshiya Kaihara ◽  
Nobutada Fujii ◽  
Daisuke Kokuryo
Keyword(s):  
Decision Making ◽  
Multiscale Modeling ◽  
Social Systems ◽  
Scale Bridging

scholarly journals High-Fidelity Agent-Based Modeling to Support Prevention Decision-Making: an Open Science Approach

2021 ◽  
Author(s):  
Wouter H. Vermeer ◽  
Justin D. Smith ◽  
Uri Wilensky ◽  
C. Hendricks Brown
Keyword(s):  
Decision Making ◽  
Social Systems ◽  
Open Science ◽  
Model Verification ◽  
High Fidelity ◽  
Agent Based ◽  
Individual Level ◽  
Adverse Health Outcomes ◽  
Modeling Process ◽  
Novel Method

AbstractPreventing adverse health outcomes is complex due to the multi-level contexts and social systems in which these phenomena occur. To capture both the systemic effects, local determinants, and individual-level risks and protective factors simultaneously, the prevention field has called for adoption of system science methods in general and agent-based models (ABMs) specifically. While these models can provide unique and timely insight into the potential of prevention strategies, an ABM’s ability to do so depends strongly on its accuracy in capturing the phenomenon. Furthermore, for ABMs to be useful, they need to be accepted by and available to decision-makers and other stakeholders. These two attributes of accuracy and acceptability are key components of open science. To ensure the creation of high-fidelity models and reliability in their outcomes and consequent model-based decision-making, we present a set of recommendations for adopting and using this novel method. We recommend ways to include stakeholders throughout the modeling process, as well as ways to conduct model verification, validation, and replication. Examples from HIV and overdose prevention work illustrate how these recommendations can be applied.

Modeling Cognitive Agents for Social Systems and a Simulation in Urban Dynamics

2009 ◽  
pp. 104-124 ◽  
Author(s):  
Yu Zhang ◽  
Mark Lewis ◽  
Christine Drennon ◽  
Michael Pellon ◽  
Coleman
Keyword(s):  
Decision Making ◽  
Social Structure ◽  
Social Systems ◽  
Three Dimensional ◽  
Decision Making Process ◽  
Social Environments ◽  
Cognitive Agents ◽  
Agent Interactions ◽  
Multi Agent ◽  
Cognitive Decision

Multi-agent systems have been used to model complex social systems in many domains. The entire movement of multi-agent paradigm was spawned, at least in part, by the perceived importance of fostering human-like adjustable autonomy and behaviors in social systems. But, efficient scalable and robust social systems are difficult to engineer. One difficulty exists in the design of how society and agents evolve and the other diffi- culties exist in how to capture the highly cognitive decision-making process that sometimes follows intuition and bounded rationality. We present a multi-agent architecture called CASE (Cognitive Agents for Social Environments). CASE provides a way to embed agent interactions in a three-dimensional social structure. It also presents a computational model for an individual agent’s intuitive and deliberative decision-making process. This chapter also presents our work on creating a multi-agent simulation which can help social and economic scientists use CASE agents to perform their tests. Finally, we test the system in an urban dynamic problem. Our experiment results suggest that intuitive decision-making allows the quick convergence of social strategies, and embedding agent interactions in a three-dimensional social structure speeds up this convergence as well as maintains the system’s stability.

scholarly journals Rational Choice Hypothesis as X-point of Utility Function and Norm Function

2020 ◽  
Vol 7 (4) ◽  
pp. 63
Author(s):  
Takeshi Kato ◽  
Yasuyuki Kudo ◽  
Junichi Miyakoshi ◽  
Jun Otsuka ◽  
Hayato Saigo ◽  
...  
Keyword(s):  
Decision Making ◽  
Utility Function ◽  
Rational Choice ◽  
Co2 Emission ◽  
Choice Model ◽  
Social Systems ◽  
Measurement Data ◽  
Current Status ◽  
Before And After ◽  
Reduction Of Co2

Towards the realization of a sustainable, fair and inclusive society, we proposed a novel decision-making model that incorporates social norms in a rational choice model from the standpoints of deontology and utilitarianism. We proposed a hypothesis that interprets choice of action as the X-point for individual utility function that increases with actions and social norm function that decreases with actions. This hypothesis is based on humans psychologically balancing the value of utility and norms in selecting actions. Using the hypothesis and approximation, we were able to isolate and infer utility function and norm function from real-world measurement data of actions on environmental conditions and elucidate the interaction between the both functions that led from current status to target actions. As examples of collective data that aggregate decision-making of individuals, we looked at the changes in power usage before and after the Great East Japan Earthquake and the correlation between national GDP and CO2 emission in different countries. The first example showed that the perceived benefits of power (i.e., utility of power usage) was stronger than the power usage restrictions imposed by norms after the earthquake, contrary to our expectation. The second example showed that a reduction of CO2 emission in each country was not related to utility derived from GDP but to norms related to CO2 emission. Going forward, we will apply this new X-point model to actual social practices involving normative problems, and design the approaches for the diagnosis, prognosis and intervention of social systems by IT systems.

scholarly journals A Game-Based Economic Model for Price Decision Making in Cyber-Physical-Social Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 111559-111576 ◽  
Author(s):  
Mingfeng Huang ◽  
Wei Liu ◽  
Tian Wang ◽  
Qingyong Deng ◽  
Anfeng Liu ◽  
...  
Keyword(s):  
Decision Making ◽  
Economic Model ◽  
Social Systems ◽  
Price Decision

How Ethics in Public Health Administration Leadership Leverages Connectedness in the age of COVID 19

2022 ◽  
Vol 2 (1) ◽  
pp. 0-0
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Ethical Decision Making ◽  
Ethical Issues ◽  
Social Systems ◽  
Moral Character ◽  
Value Systems ◽  
Organizational Cultures ◽  
Health Administration ◽  
Organizational Decision Making

Ethics is critical in emergency response to public health and patient care in ways that create a variety of challenging dilemmas and decisions. Understanding ethical codes around medical care, especially during the emergence of COVID 19, has made leadership's role in perpetuating ethical organizational cultures in healthcare vital. Ethical leadership and ethical organizational cultures transform and unite social systems around everyday purposes of ethical decision-making, leveraging organizational connectedness. Leadership value systems mitigate subjectivity constituting ethical themes of moral character and virtues to advance organizational trust. Leadership value systems reduce subjectivity, forming ethical issues of moral character and virtues to promote organizational confidence and moral organizational decision-making. This paper employs the use of content analysis from the literature to take disjointed approaches and combine them into a cohesive understanding of leadership dynamics on organizational ethics in healthcare.

Learning-Supported Decision-Making

2008 ◽  
pp. 1066-1082
Author(s):  
Elena P. Antonacopoulou ◽  
K. Nadia Papamichail
Keyword(s):  
Decision Making ◽  
Social Systems ◽  
Organizational Memory ◽  
Social Structures ◽  
Main Thrust ◽  
Social Actors ◽  
Digital Era ◽  
Technical Framework ◽  
Critical Link

The biggest challenge for any organization is managing the disperse nature of knowledge across a diverse set of knowledge carriers. The role of ICTs in supporting and extending the organizational memory is of particular concern. This chapter contributes to our understanding of the challenges the Digital era presents us by proposing a socio-technical framework, which emphasizes feedback as the critical link connecting social systems and technical structures The main thrust of the framework is the alignment of social structures and social actors in ways that seek to integrate different modes of learning with different models of decision-making. This integration is to be supported by a range of decision-learning structures (in ICT systems), which create different feedback levels. These feedback levels are the main focus of the chapter which makes a valuable contribution in extending debates of learning, decision-making and their relationship demonstrating the inherent challenges of the digital era in using ICTs as social as much as technical tools.

scholarly journals Semantics-Empowered Big Data Processing with Applications

AI Magazine ◽  
2015 ◽  
Vol 36 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Krishnaprasad Thirunarayan ◽  
Amit Sheth
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Processing ◽  
Social Systems ◽  
Intelligent Processing ◽  
Data Formats ◽  
New Concepts ◽  
Semantic Models ◽  
Trust Models

We discuss the nature of big data and address the role of semantics in analyzing and processing big data that arises in the context of physical-cyber-social systems. To handle volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle variety, we resort to semantic models and annotations of data so that intelligent processing can be done independent of heterogeneity of data formats and media. To handle velocity, we seek to use continuous semantics capability to dynamically create event or situation specific models and recognize relevant new concepts, entities and facts. To handle veracity, we explore trust models and approaches to glean trustworthiness. These four v's of big data are harnessed by the semantics-empowered analytics to derive value to support applications transcending physical-cyber-social continuum.

scholarly journals STRATEGIC ENVIRONMENTAL ASSESSMENT (SEA) OF SOCIO-ECONOMIC SYSTEMS: A SYSTEMATIC REVIEW

2013 ◽  
Vol 19 (4) ◽  
pp. 661-674 ◽  
Author(s):  
Jolanta Tamošaitienė ◽  
Oleg Kapliński
Keyword(s):  
Decision Making ◽  
Environmental Assessment ◽  
Academic Career ◽  
Data Extraction ◽  
Rational Solution ◽  
Social Systems ◽  
Strategic Environmental Assessment ◽  
Economic Systems ◽  
Multi Stage ◽  
Depth Analysis

Today, Strategic Environmental Assessment (SEA) of Socio-Economic Systems exists in micro, meso and macro environments. A complicated process is required to find a rational solution that would include a large number of problems and criteria. Therefore, existing MCDM methods must be used as well as new ones developed. Notwithstanding SEA of Analysis of Socio-Economic Processes, there is little research examining factors of use of MCDM methods; thus, a more in-depth analysis should be undertaken. This study applied a systematic search of literature. A total of 73 papers from the academic literature containing such terms as ‘Strategic Environmental Assessment (SEA)’, ‘Socio-Economic Processes (SEP)’, ‘Socio-Economic Systems (SES)’, ‘Social Systems (SS)’, ‘Economical Systems (ES)’, ‘Decision-Making (DM)’ and ‘Multi Criteria Decision-Making (MCDM)’ were identified and reviewed. As to the eligibility problem in Strategic Environmental Assessment (SEA), criteria included studies on both Social and Economic Systems & Processes that examined development and trends related to SEA of Socio-Economic Processes. MCDM methods, assessment processes, data extraction and analysis were completed in all relevant studies. General activity fields in Strategic Environmental Assessment (SEA) of Socio-Economic Systems were analysed. The key issues of SEA in micro, meso and macro environment, Socio-Economic Systems and Socio-Economic Processes factors were prominent across all researched categories. As far as the analysis of Socio-Economic Systems & Processes, decision makers should be aware of the problem in its complexity and undertake multi-stage decision-making. To honour the contribution made by Prof Valentinas Podvezko contribution in the field of Decision-Making (DM) to Strategic Environmental Assessment (SEA) of Socio-Economic Systems using MCDM methods, and to commemorate his 70th anniversary, this article also highlights his academic career and research.

DYNAMICAL CLUSTERING AS A GENERATOR OF COMPLEX SYSTEM DYNAMICS

2009 ◽  
Vol 19 (supp01) ◽  
pp. 1539-1565 ◽  
Author(s):  
ZHENYUAN ZHAO ◽  
ANDY KIROU ◽  
BŁAŻEJ RUSZCZYCKI ◽  
NEIL F. JOHNSON
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Financial Markets ◽  
Common Property ◽  
Social Systems ◽  
Biological Systems ◽  
Entire Group ◽  
Wide Range ◽  
Clustering Dynamics ◽  
Fragmentation Processes

The challenge to understand the dynamics of Complex Systems is attracting attention from a wide range of disciplines across the natural, biological and social sciences. Recent turmoil in the financial markets has brought this challenge into the public domain, with speculation rife as to the root cause of the observed fluctuations. At their heart, all Complex Systems share the common property of featuring many interacting objects from which the observed macroscopic dynamics emerge. Exactly how this happens cannot yet be specified in a generic way — however, an important milestone in this endeavor is to develop a quantitative understanding of any internal clustering dynamics within the population. Coalescence-fragmentation processes have been studied widely in conventional chemistry and physics — however, collective behavior in social systems is not limited by nearest-neighbor interactions, nor are the details of social coalescence or fragmentation processes necessarily the same as in physical and biological systems. Here we discuss the general phenomenon of coalescence and fragmentation problems with a focus on social systems in which a typical fragmentation process corresponds to an entire group breaking up, as opposed to the typical binary splitting studied in physical and biological systems. Having discussed situations under which power-laws for the group distribution size emerge from such internal clustering dynamics, we move on to look at the specific application to financial markets. We propose a new model for financial market dynamics based on the combination of internal clustering (i.e. herding) dynamics with human decision-making. The resulting fluctuation in price movements is closer to what is observed empirically, leading us to speculate that the combination of dynamical clustering and decision-making are key for developing quantitative models of social dynamical phenomena.

Sign in / Sign up

Export Citation Format

Share Document