AROUND THE EMPIRICAL AND INTENTIONAL REFERENCES OF AGENT-BASED SIMULATION IN THE SOCIAL SCIENCES

2006 ◽  
Keyword(s):  
Social Sciences ◽  
Agent Based Simulation ◽  
Agent Based ◽  
The Social

scholarly journals Special Issue on New Trends in Agent-Based Simulation

2011 ◽  
Vol 15 (2) ◽  
pp. 165-165
Author(s):  
Keiki Takadama ◽  
Kiyoshi Izumi
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Computer Science ◽  
Mutual Influence ◽  
Real Data ◽  
Special Issue ◽  
Learning Mechanisms ◽  
Agent Based Simulation ◽  
Agent Based ◽  
The Social

Agent-Based Simulation (ABS), an interdisciplinary area embracing both the computer science and the social science, has attracted much attention and aided the understanding of socially complex phenomena. A current important issue in this research area is how to improve ABS effectiveness and comprehension, which makes further mutual influence between the computer science and the social sciences indispensable - e.g., (1) agent modeling involving learning mechanisms in the computer science and (2) social dynamics analysis needed in the social science. Such integration of these two areas would help fulfill the great potential of ABS, first in solving complex engineering problems using agent-based technology and second in developing and testing new theories on socially complex systems. This special issue features ABS papers from both of these important areas exploring new trends in ABS. The 10 papers composing this special issue start with papers by Nobutada Fujii and Hiroyasu Inoue analyzing the relationship between the network structure and system dynamics. In these papers, an agent-based computational economics approach has been active in applying agent-based technologies to financial and economic systems. Papers by Biliana Alexandrova-Kabadjova, Isamu Okada, TomokoOhi, and Nariaki Nishino cover consumer and financial markets using agent-based models. They test economic theory and examine market phenomena for market design. Agent-based simulation is increasingly used in application fields in the social sciences. Papers by Kiyoshi Izumi, Hideki Fujii, Hiromitsu Hattori, and Shigeo Sagai propose solutions for actual social problems such as injury prevention, traffic, and electrical power. Models are created based on behavior data, and the integration of an agent-based model and real data is a hot topic in this area. As the beginning of these technical papers, this issue starts by a position paper to give an ABS overview for understanding important issues in ABS from an overall viewpoint and for understanding state-of-the-art ABS. The information presented is invaluable in helping readers grasp the important features of ABS.

scholarly journals Application of Agent-based Modeling for Cultural Information-based Decisions Making

2020 ◽  
Vol 88 ◽  
pp. 8-28
Author(s):  
Rimvydas Laužikas ◽  
Darius Plikynas ◽  
Vytautas Dulskis ◽  
Leonidas Sakalauskas ◽  
Arūnas Miliauskas
Keyword(s):  
Social Capital ◽  
Simulation Model ◽  
Cultural Participation ◽  
Agent Based Simulation ◽  
Research Issues ◽  
Agent Based ◽  
Cultural Events ◽  
The Social ◽  
Cultural Processes ◽  
The Impact

The impact of cultural processes on personal and social changes is one of the important research issues not only in contemporary social sciences but also for simulation of future development scenarios and evidence-based policy decision making. In the context of the theoretical concept of cultural values, based on the system theory and theory of social capital, the impact of cultural events could be analyzed and simulated by focussing on the construction/deconstruction of social capital, which takes place throughout the actor’s cultural participation. The main goal of this research is the development of measuring metrics, and agent-based simulation model aimed at investigation of the social impact of cultural processes.  This paper provides new insights of modeling the social capital changes in a society and its groups, depending on cultural participation. The proposed measurement metrics provide the measurement facility of three key components: actors, cultural events and events flow and social capital. It provides the initial proof of concept simulation results, - simplified agent-based simulation model showcase. The NetLogo MAS platform is used as a simulation environment.  

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.

scholarly journals The Potential of Modeling Process for Social Sciences and Social Work

2021 ◽  
pp. 113-134
Author(s):  
Andrés Lorenzo-Aparicio ◽  
Keyword(s):  
Social Sciences ◽  
Social Workers ◽  
Social Processes ◽  
Social Phenomena ◽  
Agent Based ◽  
Useful Knowledge ◽  
Agent Based Modelling ◽  
Modeling Process ◽  
The Social ◽  
Human Ecosystems

Simplification and necessary reductionism in a model cannot lead to detailed descriptions of social phenomena with all their complexity, but we can obtain useful knowledge from their application both in specific and generic contexts. Human ecosystems, that perform as adaptative complex systems, have features which make it difficult to generate valid models. Amongst them, the emergency phenomena, that presents new characteristics that cannot be explained by the components of the system itself. But without this knowledge derived from modelling, we, as social workers, cannot suggest answers that ignore the structural causes of social problems. Faced with this challenge we propose Agent Based Modelling, as it allows us to study the social processes of human ecosystems and in turn demonstrates new challenges of knowledge and competences that social workers might have.

scholarly journals Autonomous Agents in 3D Crowd Simulation Through BDI Architecture

2021 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Sim Keng Wai ◽  
Cheah WaiShiang ◽  
Muhammad Asyraf Bin Khairuddin ◽  
Yanti Rosmunie Binti Bujang ◽  
Rahmat Hidayat ◽  
...  
Keyword(s):  
Social Sciences ◽  
Autonomous Agents ◽  
Crowd Simulation ◽  
Agent Architecture ◽  
Agent Based ◽  
Interacting Agents ◽  
The Social ◽  
Bush Fire ◽  
Bdi Architecture

Agent based simulation (ABS) is a paradigm to modelling systems included of autonomous and interacting agents. ABS has been tremendous growth and used by researchers in the social sciences to study socio-environmental complex systems. To date, various platforms have been introduced for agent-based social simulation. They are rule based in any logic, python based in SPADE and etc. Although those platforms have been introduced, there is still an insufficient to develop a crowd simulation in 3D platform. Having a 3D platform is needed to enabling the crowd simulation for training purposes. However, the current tools and platform still lack features to develop and simulate autonomous agents in the 3D world. This paper introduced a BDI plug in at Unity3D for crowd simulation. BDI is an intelligent agent architecture and it is able to develop autonomous agents in crowd environment. In this paper, we present the BDI plug with a case study of Australia bush fire and discuss a method to support autonomous agents' development in 3D crowd simulation. The tool allows the modeller to develop autonomous agents in 3D world by taking the advantages of Unity3D.

Analysis and synthesis: multi-agent systems in the social sciences

2012 ◽  
Vol 27 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Robert E. Marks
Keyword(s):  
Social Sciences ◽  
Computer Science ◽  
Common Source ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Social ◽  
Analysis And Synthesis ◽  
Multi Agent ◽  
Computational Systems

AbstractAlthough they flow from a common source, the uses of multi-agent systems (or ‘agent-based computational systems’––ACE) vary between the social sciences and computer science. The distinction can be broadly summarized as analysis versus synthesis, or explanation versus design. I compare and contrast these uses, and discuss sufficiency and necessity in simulations in general and in multi-agent systems in particular, with a computer science audience in mind.

scholarly journals BDI agents in social simulations: a survey

2016 ◽  
Vol 31 (3) ◽  
pp. 207-238 ◽  
Author(s):  
Carole Adam ◽  
Benoit Gaudou
Keyword(s):  
Social Sciences ◽  
Folk Psychology ◽  
Modelling And Simulation ◽  
Human Behaviour ◽  
Bdi Agents ◽  
Agent Based ◽  
The Social ◽  
Reactive Particle

AbstractModelling and simulation have long been dominated by equation-based approaches, until the recent advent of agent-based approaches. To curb the resulting complexity of models, Axelrod promoted the KISS principle: ‘Keep It Simple, Stupid’. But the community is divided and a new principle appeared: KIDS, ‘Keep It Descriptive, Stupid’. Richer models were thus developed for a variety of phenomena, while agent cognition still tends to be modelled with simple reactive particle-like agents. This is not always appropriate, in particular in the social sciences trying to account for the complexity of human behaviour. One solution is to model humans as belief, desire and intention (BDI) agents, an expressive paradigm using concepts from folk psychology, making it easier for modellers and users to understand the simulation. This paper provides a methodological guide to the use of BDI agents in social simulations, and an overview of existing methodologies and tools for using them.

scholarly journals GETTING AWAY FROM NUMBERS: USING QUALITATIVE OBSERVATION FOR AGENT-BASED MODELING

2008 ◽  
Vol 11 (02) ◽  
pp. 175-185 ◽  
Author(s):  
LU YANG ◽  
NIGEL GILBERT
Keyword(s):  
Social Sciences ◽  
Quantitative Data ◽  
Qualitative Data ◽  
Participant Observation ◽  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Qualitative Observation

Although in many social sciences there is a radical division between studies based on quantitative (e.g. statistical) and qualitative (e.g. ethnographic) methodologies and their associated epistemological commitments, agent-based simulation fits into neither camp, and should be capable of modelling both quantitative and qualitative data. Nevertheless, most agent-based models (ABMs) are founded on quantitative data. This paper explores some of the methodological and practical problems involved in basing an ABM on qualitative participant observation and proposes some advice for modelers.

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