Log in

Relevant bibliographies by topics / Social simulation / Journal articles

To see the other types of publications on this topic, follow the link: Social simulation.

Journal articles on the topic 'Social simulation'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Social simulation.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Dickinson, Melanie, Noah Wardrip-Fruin, and Michael Mateas. "Social Simulation for Social Justice." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 13, no. 2 (June 25, 2021): 61–68. http://dx.doi.org/10.1609/aiide.v13i2.12982.

Full text

Abstract:

We argue that social simulation can help us understand social justice issues. In particular, modeling certain social dynamics within computational systems can be used to creatively explore and better understand the social and identity dynamics of oppression. Writing theories of oppression in code forces us to explicate everything, and question what we leave out or what we can’t account for. As an early step in this direction, we present an in-progress social simulation of group discussion in activist meetings, developed in the already-existing AI system, Ensemble. Through this minimal, highly constrained social arena, we can explore wide-reaching phenomena like privilege, intersectionality, and power dynamics in nonhierarchical groups, but in a way that’s grounded in concrete, person-to-person interactions. We propose that this kind of social simulation can aid in the process of unlearning hegemonic ways of being, and imagining liberatory alternatives.

APA, Harvard, Vancouver, ISO, and other styles

2

Zayceva, Ol'ga, and Pavel Katyshev. "Social Parameters in the Genre of Communicative Simulation." Virtual Communication and Social Networks 2023, no. 4 (June 2, 2023): 215–21. http://dx.doi.org/10.21603/2782-4799-2023-2-4-215-221.

Full text

Abstract:

Communicative simulation is a virtual practice that reproduces offline forms of social interaction using information and communication technologies. This research parametrized communicative simulation genres and described the interpersonal aspect of virtual interaction in a virtual environment, i.e., bricolage form, intersemiotics, and reduced corporality. Communicative simulations differ from such social practices as offline simulations or role games. The social aspect of communicative simulations includes (1) the media nature of virtual interaction; (2) the hybrid nature of communicative simulations that combines the features of both ordinary simulations and text-based role games; (3) the dual nature of social interaction, carried out simultaneously in material and diegetic spaces. As a result, the social aspect of communicative simulation can be presented in the form of a three-level model: material, diegeological, instrumental levels.

APA, Harvard, Vancouver, ISO, and other styles

3

Squazzoni, Flaminio, Wander Jager, and Bruce Edmonds. "Social Simulation in the Social Sciences." Social Science Computer Review 32, no. 3 (December 6, 2013): 279–94. http://dx.doi.org/10.1177/0894439313512975.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Boskma, P. "SOCIAL IMPACT ASSESSMENT BY SOCIAL SIMULATION." Impact Assessment 4, no. 3-4 (March 1986): 133–48. http://dx.doi.org/10.1080/07349165.1986.9725781.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Badcock, Christopher, Nigel Gilbert, and Jim Doran. "Simulating Societies: The Computer Simulation of Social Phenomena." British Journal of Sociology 46, no. 3 (September 1995): 544. http://dx.doi.org/10.2307/591863.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Bollen, Kenneth A., Nigel Gilbert, and Jim Doran. "Simulating Societies: The Computer Simulation of Social Phenomena." Social Forces 74, no. 2 (December 1995): 745. http://dx.doi.org/10.2307/2580509.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Steinmetz, Janina, Brittany M. Tausen, and Jane L. Risen. "Mental Simulation of Visceral States Affects Preferences and Behavior." Personality and Social Psychology Bulletin 44, no. 3 (November 21, 2017): 406–17. http://dx.doi.org/10.1177/0146167217741315.

Full text

Abstract:

Preferences and behavior are heavily influenced by one’s current visceral experience, yet people often fail to anticipate such effects. Although research suggests that this gap is difficult to overcome—to act as if in another visceral state—research on mental simulation has demonstrated that simulations can substitute for experiences, albeit to a weaker extent. We examine whether mentally simulating visceral states can impact preferences and behavior. We show that simulating a specific visceral state (e.g., being cold or hungry) shifts people’s preferences for relevant activities (Studies 1a-2) and choices of food portion sizes (Study 3). Like actual visceral experiences, mental simulation only affects people’s current preferences but not their general preferences (Study 4). Finally, people project simulated states onto similar others, as is the case for actual visceral experiences (Study 5). Thus, mental simulation may help people anticipate their own and others’ future preferences, thereby improving their decision making.

APA, Harvard, Vancouver, ISO, and other styles

8

Azad, Sasha, Jennifer Wellnitz, Luis Garcia, and Chris Martens. "Anthology: A Social Simulation Framework." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 18, no. 1 (October 11, 2022): 224–31. http://dx.doi.org/10.1609/aiide.v18i1.21967.

Full text

Abstract:

Social simulation research seeks to understand the dynamics of complex human behavior by simulating populations of individual decision-makers as multi-agent systems. However, prior work in games and entertainment fail to account for interactions between social behavior, geography, and relationships in a manner that allows researchers to easily reuse their frameworks and model social characters. We present Anthology, an extensible software framework for modeling human social systems, within the context of an ongoing research agenda to integrate AI techniques from social simulation games and computational social science to enable researchers to model and reason about the complex dynamics of human social behavior. Anthology comprises a motive-based agent decision making algorithm; a knowledge representation system for relationships; a flexible specification language for precondition-effect-style actions; a user interface to inspect and interact with the simulation as it runs in real-time; and an extensive user documentation and reference manual. We describe our participatory research design process used for the developing Anthology, the state of the current system, it's limitations and our future development directions.

APA, Harvard, Vancouver, ISO, and other styles

9

TOKUYASU, Akira. "Is Social Simulation Possible?" TRENDS IN THE SCIENCES 17, no. 2 (2012): 2_54–2_57. http://dx.doi.org/10.5363/tits.17.2_54.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Bronson, Richard, and Chanoch Jacobsen. "Simulation and social theory." SIMULATION 47, no. 2 (August 1986): 58–62. http://dx.doi.org/10.1177/003754978604700202.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Birkin, Mark, Rob Procter, Rob Allan, Sean Bechhofer, Iain Buchan, Carole Goble, Andy Hudson-Smith, Paul Lambert, David De Roure, and Richard Sinnott. "Elements of a computational infrastructure for social simulation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1925 (August 28, 2010): 3797–812. http://dx.doi.org/10.1098/rsta.2010.0145.

Full text

Abstract:

Applications of simulation modelling in social science domains are varied and increasingly widespread. The effective deployment of simulation models depends on access to diverse datasets, the use of analysis capabilities, the ability to visualize model outcomes and to capture, share and re-use simulations as evidence in research and policy-making. We describe three applications of e-social science that promote social simulation modelling, data management and visualization. An example is outlined in which the three components are brought together in a transport planning context. We discuss opportunities and benefits for the combination of these and other components into an e-infrastructure for social simulation and review recent progress towards the establishment of such an infrastructure.

APA, Harvard, Vancouver, ISO, and other styles

12

Harada, Takuya, and Tadahiko Murata. "Ensuring Reproducible Simulations on Heterogeneous Computing Environments for Social Simulation." Transactions of the Institute of Systems, Control and Information Engineers 31, no. 2 (February 15, 2018): 37–48. http://dx.doi.org/10.5687/iscie.31.37.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Bordogna, Clelia M., and Ezequiel V. Albano. "Simulation of social processes: application to social learning." Physica A: Statistical Mechanics and its Applications 329, no. 1-2 (November 2003): 281–86. http://dx.doi.org/10.1016/s0378-4371(03)00601-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Wu, Jiang, Hou Zhu, Menglin Yin, and Xin Luo. "A Review for the Validation of Social Simulation on Artificial Social Organization." International Journal of Agent Technologies and Systems 4, no. 2 (April 2012): 22–41. http://dx.doi.org/10.4018/jats.2012040102.

Full text

Abstract:

Social simulation on artificial social organization, which uses computer simulation to construct artificial society to research social organization, has been becoming popular. Validation of simulation can improve the accuracy, credibility and applicability in the modeling and simulation, and is the key step to apply social organizational model. In this paper, the current research of simulation validation is reviewed, the category of social simulation is defined, and philosophical perspective of simulation validation is analyzed. Implementations of simulation validation in various models, including framework, level, type and technology, are introduced as well. Then, the validation in social simulation, including features, existing problems, framework and techniques, is analyzed in particular. Finally, the further work for the simulation validation is announced.

APA, Harvard, Vancouver, ISO, and other styles

15

Squazzoni, Flaminio, and Bruce Edmonds. "Symposium Issue on Social Simulation." Social Science Computer Review 32, no. 3 (December 6, 2013): 275–78. http://dx.doi.org/10.1177/0894439313512972.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Sawyer, R. Keith. "Social explanation and computational simulation." Philosophical Explorations 7, no. 3 (September 2004): 219–31. http://dx.doi.org/10.1080/1386979042000258321.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Deering, Shad. "Forceps, Simulation, and Social Media." Obstetrics & Gynecology 128, no. 3 (September 2016): 425–26. http://dx.doi.org/10.1097/aog.0000000000001612.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Harrison, J. Richard. "Simulation in the Social Sciences." Simulation Modelling Practice and Theory 16, no. 2 (February 2008): 173–74. http://dx.doi.org/10.1016/j.simpat.2007.11.014.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Oatley, Keith. "Fiction: Simulation of Social Worlds." Trends in Cognitive Sciences 20, no. 8 (August 2016): 618–28. http://dx.doi.org/10.1016/j.tics.2016.06.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Lane, Justin E., and F. LeRon Shults. "Cognition, Culture, and Social Simulation." Journal of Cognition and Culture 18, no. 5 (November 28, 2018): 451–61. http://dx.doi.org/10.1163/15685373-12340039.

Full text

Abstract:

AbstractThe use of modeling and simulation (M&S) methodologies is growing rapidly across the psychological and social sciences. After a brief introduction to the relevance of computational methods for research on human cognition and culture, we describe the sense in which computer models and simulations can be understood, respectively, as “theories” and “predictions.” Most readers of JoCC are interested in integrating micro- and macro-level theories and in pursuing empirical research that informs scientific predictions, and we argue that M&S provides a powerful new set of tools for pursuing these interests. We also point out the way in which M&S can help scholars of cognition and culture address four key desiderata for social scientific research related to the themes of clarity, falsifiability, dynamicity, and complexity. Finally, we provide an introduction to the other papers that comprise this special issue, which includes contributions on topics such as the role of M&S in interdisciplinary debates, shamanism, early Christian ritual practices, the emergence of the Axial age, and the social scientific appropriation of algorithms from massively multiplayer online games.

APA, Harvard, Vancouver, ISO, and other styles

21

Mollona, Edoardo. "Computer simulation in social sciences." Journal of Management & Governance 12, no. 2 (May 2008): 205–11. http://dx.doi.org/10.1007/s10997-008-9049-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Brynielsson, Joel, Lisa Kaati, and Pontus Svenson. "Social positions and simulation relations." Social Network Analysis and Mining 2, no. 1 (June 29, 2011): 39–52. http://dx.doi.org/10.1007/s13278-011-0032-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Squazzoni, Flaminio. "Special issue on: Social simulation." Mind & Society 8, no. 2 (July 14, 2009): 131–34. http://dx.doi.org/10.1007/s11299-009-0066-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Conte, Rosaria. "Special issue on: Social simulation." Mind & Society 8, no. 2 (July 15, 2009): 127–30. http://dx.doi.org/10.1007/s11299-009-0067-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Khakhanova, Hanna, and Vugar Abdullayev. "DIGITAL SIMULATION OF SOCIAL PROCESSES." Computer Design Systems. Theory and Practice 5, no. 1 (2023): 47–56. http://dx.doi.org/10.23939/cds2023.01.047.

Full text

Abstract:

Implementing cyber-social computing components and cloud management services based on metric cyber-physical monitoring for social processes is aimed at creating a cyber-state to ensure a high quality of life for citizens. Logical schemes of cyber-social computing are provided for creating a cyber-physical structure of cloud management for the university based on metric digital monitoring of scientific and educational processes. The synthesis and analysis of socio-logical structures is aimed at predicting the consequences of adopting managerial influences. The algorithm of electronic document circulation is presented as a closed technology for the production and application of a paperless document stored on the cloud or in the corporate network, which consists in its coordination by all services and delivery to addressees in the space of e-Document Circulation.

APA, Harvard, Vancouver, ISO, and other styles

26

Von Bülow, Katherina. "Simulation-based mathematics and social justice activities." Prometeica - Revista de Filosofía y Ciencias, no. 27 (July 27, 2023): 316–26. http://dx.doi.org/10.34024/prometeica.2023.27.15303.

Full text

Abstract:

In this paper, various dimensions of care involved in mathematics education are linked to the need to develop classroom activities that connect mathematics and social justice issues. Drawing from literature that shows cognition is situated and embodied, the importance of meaningful contextualization and social interaction when learning mathematics is highlighted. The concept of “simulation-based mathematics and social justice activities” is presented as an approach for the work of bringing social justice issues that have mathematics at their core to the classroom. Theoretical constructs and examples are discussed, to illustrate what such simulations may entail and what may be learned from scholars, in different educational fields, who use simulations in classroom activities. Potentially beneficial features of social justice simulations are related to various educational goals, such as: decreasing arbitrary boundaries between mathematical sub-areas and between mathematics and other disciplines; providing opportunities for choice and the embodiment of different perspectives; and offering opportunities for inter-personal learning. I report on a simulation-based mathematics and social justice activity, conducted in a teacher education classroom. Students—in this case future teachers—were prompted to write reflectively about their participation in the activity. My interest lies in finding out what, if any, cognitive and affective benefits these prospective teachers connect with their experience of mathematics in the activity. To investigate this, I analyze six themes that are present in the data and illustrate each theme using excerpts of student writing. The thematic analysis allows us to learn about connections made by these students, between mathematics, in the context of the activity, and issues that are personally meaningful to them, such as: their own future teaching practice, learning and interacting with peers, beliefs and feelings about mathematics and the learning of mathematics, and different perspectives on complex decisions, involving cooperation or lack thereof, that are encountered in real life situations.

APA, Harvard, Vancouver, ISO, and other styles

27

Yan, Dapeng, Gangyi Ding, Kexiang Huang, Chongzhi Bai, Lian He, and Longfei Zhang. "Enhanced Crowd Dynamics Simulation with Deep Learning and Improved Social Force Model." Electronics 13, no. 5 (February 29, 2024): 934. http://dx.doi.org/10.3390/electronics13050934.

Full text

Abstract:

The traditional social force model (SFM) in crowd simulation experiences difficulty coping with the complexity of the crowd, limited by singular physical formulas and parameters. Recent attempts to combine deep learning with these models focus more on simulating specific states of crowds. This paper introduces an advanced deep social force model, influenced by crowd states. It utilizes deep neural networks to accurately fit crowd trajectory features, enhancing behavior simulation capabilities. Geometrical constraints within the model provide control over varied crowd behaviors, adjustable to simulate different crowd types. Before training, we use the SFM to refine behaviors in real trajectories with excessively small distances, aiming to enhance the general applicability of the model. Comparative experiments affirm the effectiveness of the model, showing comparable performance to both classic physical models and modern learning-based hybrid models in pedestrian simulations, with reduced collisions. In addition, the model has a certain ability to simulate crowds with high density and diverse behaviors.

APA, Harvard, Vancouver, ISO, and other styles

28

Tolk, Andreas, Wesley J. Wildman, F. LeRon Shults, and Saikou Y. Diallo. "Human Simulation as the Lingua Franca for Computational Social Sciences and Humanities: Potential and Pitfalls." Journal of Cognition and Culture 18, no. 5 (November 28, 2018): 462–82. http://dx.doi.org/10.1163/15685373-12340040.

Full text

Abstract:

AbstractThe social sciences and humanities are fragmented into specialized areas, each with their own parlance and procedures. This hinders information sharing and the growth of a coherent body of knowledge. Modeling and simulation can be the scientific lingua franca, or shared technical language, that can unite, integrate, and relate relevant parts of these diverse disciplines.Models are well established in the scientific community as mediators, contributors, and enablers of scientific knowledge. We propose a potentially revolutionary linkage between social sciences, humanities and computer simulation, forging what we call “human simulation.” We explore three facets of human simulation, namely: (1) the simulation of humans, (2) the design of simulations for human use, and (3) simulations that include humans as well as simulated agents among the actors. We describe the potential of human simulation using several illuminating examples. We also discuss computational, epistemological, and hermeneutical challenges constraining the use of human simulation.

APA, Harvard, Vancouver, ISO, and other styles

29

Stokoe, Elizabeth. "Social psychology and social interaction: Identities, simulation and application." Social Psychological Review 16, no. 1 (2014): 20–33. http://dx.doi.org/10.53841/bpsspr.2014.16.1.20.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Sun, Ron, and Isaac Naveh. "Social institution, cognition, and survival: a cognitive–social simulation." Mind & Society 6, no. 2 (February 22, 2007): 115–42. http://dx.doi.org/10.1007/s11299-007-0027-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Hox, Joop J. "Computational Social Science Methodology, Anyone?" Methodology 13, Supplement 1 (June 1, 2017): 3–12. http://dx.doi.org/10.1027/1614-2241/a000127.

Full text

Abstract:

Abstract. This article reviews computational social science methods and their relation to conventional methodology and statistics. Computational social science has three important features. Firstly, it often involves big data; data sets so large that conventional database and analysis techniques cannot handle them with ease. Secondly, dealing with these big data sets has given rise to analysis techniques that are specially developed for big data. Given the size of the data, resampling and cross-validation approaches become feasible that allow both data-driven exploration and checks on overfitting the data. A third important feature is simulation, especially agent-based simulation. Here size also matters. Agent-based simulation is well known in social science, but modern computer equipment and software allows simulations of unprecedented scale. Many of these techniques, especially the resampling and cross-validation approaches, are potentially very useful for social scientists. Given the relatively small size of social science “big data” is useful to explore how well these techniques perform with smaller data sets. Social science methodology can contribute to this field by exploring if well-known methodological distinctions between external validity, internal validity, and construct validity can help clear up discussions on data quality (veracity) in computational social science.

APA, Harvard, Vancouver, ISO, and other styles

32

Wolfe-Taylor, Samantha N., Khadija Khaja, David Wilkerson, and Christian K. Deck. "Future of Social Work Education." Advances in Social Work 22, no. 2 (November 8, 2022): 287–302. http://dx.doi.org/10.18060/24912.

Full text

Abstract:

Advances in technology, an increase in non-traditional students, a new generation of e-learners, the COVID-19 pandemic’s impact on education and practice, and the emergence of greater practitioner and client adoption of telebehavioral health present opportunities and challenges for curricular innovation in schools of social work. e-Simulations are reliable, valid, authentic high impact practices that address these challenges and prepare students for a future where social workers are called upon to adopt telebehavioral practice. Although there is literature on the development, implementation, and assessment of simulation-based learning in social work education, much of the literature explores the use of simulations in face-to-face social work education. Provided is a guide for educators and administrators on developing, implementing, and assessing online simulations (e-simulations) in social work education.

APA, Harvard, Vancouver, ISO, and other styles

33

Rahman, Arief, Sri Gunani Partiwi, Ratna Sari Dewi, and Naning Aranti Wessiani. "Measuring the social impact on employee engagement using agent-based simulation." Salud, Ciencia y Tecnología 2, S2 (December 31, 2022): 188. http://dx.doi.org/10.56294/saludcyt2022188.

Full text

Abstract:

Employee Engagement is a pattern of human interaction in an organization that presents excitement, dedication, and comfort in the work environment: the higher employee engagement, the more efficient way to reach the goals. Measuring the impact of employee interaction on employee engagement became essential for the organization. This study applied the social impact model to describe the interaction patterns of employees within an organization, including the intervention of leaders in groups. The agent-based simulation is constructed to simulate the behavior and interaction patterns. This study assessed the impact of 4 employee engagement aspects: recognition, care, commitment, and best friend. Agent leader and agent employee were the two primary roles of the simulation. The employee engagement survey has conducted by our university with more than 380 respondents, including the leader and staff. New trait adoption role as a pattern of employee engagement interaction has been formulated in this study and becomes a state of change of agent behavior in simulations. The level of employee engagement can be calculated and displayed in the dynamics of change with agent-based simulations. The four aspects of employee engagement show the effect of increasing the level of engagement with a variety of different patterns.

APA, Harvard, Vancouver, ISO, and other styles

34

Matsui, Hiroyuki. "Agent Based Simulation in Social Science." TRENDS IN THE SCIENCES 10, no. 6 (2005): 84–85. http://dx.doi.org/10.5363/tits.10.6_84.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

NODA, Itsuki. "Multiagent Social Simulation for Emergency Evacuation." TRENDS IN THE SCIENCES 23, no. 3 (March 1, 2018): 3_42–3_47. http://dx.doi.org/10.5363/tits.23.3_42.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Fujita, Rieko, Tokuro Matsuo, Tetsuya Oishi, and Teruhisa Hochin. "Lobbying Simulation Issues in Social Science." Information Engineering Express 2, no. 4 (2016): 53–61. http://dx.doi.org/10.52731/iee.v2.i4.141.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

TERANO, Takao. "How to Convince Social Simulation Technologies." TRENDS IN THE SCIENCES 17, no. 2 (2012): 2_45–2_47. http://dx.doi.org/10.5363/tits.17.2_45.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Garson, G. David. "Computerized Simulation in the Social Sciences." Simulation & Gaming 40, no. 2 (May 7, 2008): 267–79. http://dx.doi.org/10.1177/1046878108322225.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Sun, Ron. "Cognitive Social Simulation for Policy Making." Policy Insights from the Behavioral and Brain Sciences 5, no. 2 (August 21, 2018): 240–46. http://dx.doi.org/10.1177/2372732218785925.

Full text

Abstract:

Cognitive social simulation is at the intersection of cognitive modeling and social simulation, two forms of computer-based, quantitative modeling and understanding. Cognitive modeling centers on producing precise computational or mathematical models of mental processes (such as human reasoning or decision making), while social simulation focuses on precise models of social processes (such as group discussion or collective decision making). By combining cognitive and social models, cognitive social simulation is poised to address issues concerning both individual and social processes. To better anticipate the implications of policies, detailed simulation enables precise analysis of possible scenarios and outcomes. Thus, cognitive social simulation will have practical applications in relation to policy making in many areas that require understanding at both the individual and the aggregate level.

APA, Harvard, Vancouver, ISO, and other styles

40

Oden, Kevin B., Peter Terrence, and Jeff Stahl. "Social Influence in a Distributed Simulation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 50, no. 17 (October 2006): 1779–83. http://dx.doi.org/10.1177/154193120605001712.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

O'Sullivan, Terence. "Simulation games and social work education." Social Work Education 7, no. 3 (June 1988): 12–16. http://dx.doi.org/10.1080/02615478811220161.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Krueger, Joachim I. "Social projection between theory and simulation." New Ideas in Psychology 30, no. 3 (December 2012): 325–27. http://dx.doi.org/10.1016/j.newideapsych.2012.01.003.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Sun, Ron. "Cognitive Social Simulation Incorporating Cognitive Architectures." IEEE Intelligent Systems 22, no. 5 (September 2007): 33–39. http://dx.doi.org/10.1109/mis.2007.4338492.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Lasquety-Reyes, Jeremiah A. "Towards Computer Simulations of Virtue Ethics." Open Philosophy 2, no. 1 (September 26, 2019): 399–413. http://dx.doi.org/10.1515/opphil-2019-0029.

Full text

Abstract:

AbstractThis article presents two approaches for computer simulations of virtue ethics in the context of agent-based modeling, a simple way and a complex way. The simple way represents virtues as numeric variables that are invoked in specific events or situations. This way can easily be implemented and included in social simulations. On the other hand, the complex way requires a PECS framework: physical, cognitive, emotional, and social components need to be implemented in agents. Virtue is the result of the interaction of these internal components rather than a single variable. I argue that the complex way using the PECS framework is more suitable for simulating virtue ethics theory because it can capture the internal struggle and conflict sometimes involved in the practice of virtue. To show how the complex way could function, I present a sample computer simulation for the cardinal virtue of temperance, the virtue that moderates physical desires such as food, drink, and sex. This computer simulation is programmed in Python and builds upon the well-known Sugarscape simulation.1

APA, Harvard, Vancouver, ISO, and other styles

45

Chen, Hongyi, Jingtao Ding, Yong Li, Yue Wang, and Xiao-Ping Zhang. "Social Physics Informed Diffusion Model for Crowd Simulation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 1 (March 24, 2024): 474–82. http://dx.doi.org/10.1609/aaai.v38i1.27802.

Full text

Abstract:

Crowd simulation holds crucial applications in various domains, such as urban planning, architectural design, and traffic arrangement. In recent years, physics-informed machine learning methods have achieved state-of-the-art performance in crowd simulation but fail to model the heterogeneity and multi-modality of human movement comprehensively. In this paper, we propose a social physics-informed diffusion model named SPDiff to mitigate the above gap. SPDiff takes both the interactive and historical information of crowds in the current timeframe to reverse the diffusion process, thereby generating the distribution of pedestrian movement in the subsequent timeframe. Inspired by the well-known social physics model, i.e., Social Force, regarding crowd dynamics, we design a crowd interaction encoder to guide the denoising process and further enhance this module with the equivariant properties of crowd interactions. To mitigate error accumulation in long-term simulations, we propose a multi-frame rollout training algorithm for diffusion modeling. Experiments conducted on two real-world datasets demonstrate the superior performance of SPDiff in terms of both macroscopic and microscopic evaluation metrics. Code and appendix are available at https://github.com/tsinghua-fib-lab/SPDiff.

APA, Harvard, Vancouver, ISO, and other styles

46

OHTA, Toshizumi. "Social Media and Social Simulation: Strategic Upward Spiral of Knowledge." TRENDS IN THE SCIENCES 17, no. 2 (2012): 2_48–2_49. http://dx.doi.org/10.5363/tits.17.2_48.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Merten, Peter P. "Systems simulation. The simulation of social system evolution with spiral loops." Behavioral Science 33, no. 2 (April 1988): 131–57. http://dx.doi.org/10.1002/bs.3830330205.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Bonabeau, Eric. "Business Applications of Social Agent-Based Simulation." Advances in Complex Systems 03, no. 01n04 (January 2000): 451–61. http://dx.doi.org/10.1142/s0219525900000315.

Full text

Abstract:

Agent-based simulation is a powerful simulation modeling technique that has seen a number of applications in the last five years, including applications to real-world business problems. In this chapter I introduce agent-based simulation and review three applications to business problems: a theme park simulation, a stock market simulation, and a bankwide simulation.

APA, Harvard, Vancouver, ISO, and other styles

49

Adam, Carole, and Benoit Gaudou. "BDI agents in social simulations: a survey." Knowledge Engineering Review 31, no. 3 (June 2016): 207–38. http://dx.doi.org/10.1017/s0269888916000096.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

50

Barsalou, Lawrence W. "Simulation, situated conceptualization, and prediction." Philosophical Transactions of the Royal Society B: Biological Sciences 364, no. 1521 (May 12, 2009): 1281–89. http://dx.doi.org/10.1098/rstb.2008.0319.

Full text

Abstract:

Based on accumulating evidence, simulation appears to be a basic computational mechanism in the brain that supports a broad spectrum of processes from perception to social cognition. Further evidence suggests that simulation is typically situated, with the situated character of experience in the environment being reflected in the situated character of the representations that underlie simulation. A basic architecture is sketched of how the brain implements situated simulation. Within this framework, simulators implement the concepts that underlie knowledge, and situated conceptualizations capture patterns of multi-modal simulation associated with frequently experienced situations. A pattern completion inference mechanism uses current perception to activate situated conceptualizations that produce predictions via simulations on relevant modalities. Empirical findings from perception, action, working memory, conceptual processing, language and social cognition illustrate how this framework produces the extensive prediction that characterizes natural intelligence.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!