The Ethics of Agent-Based Social Simulation

Anzola, David; Barbrook-Johnson, Pete; Gilbert, Nigel

doi:10.18564/jasss.4907

Cited by 6 publications

(3 citation statements)

References 70 publications

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“…In agent‐based modeling work outside of community psychology, researchers have developed participatory processes (Naivinit et al, 2009; Petrosino et al, 2018; Zellner et al, 2012), including the companion modeling process, which brings stakeholders together to cyclically define a modeling problem, establish a model, and interpret results (Étienne, 2014). This approach is helpful for both generating knowledge about a problem and supporting stakeholders in making collective decisions (Barnaud et al, 2013; Étienne, 2014; Ramanath & Gilbert, 2004). Community‐engaged role‐playing games that help uncover the micro‐level behaviors that aggregate to form macro‐level phenomena are also an approach to developing models with community members (Voinov & Bousquet, 2010).…”

Section: Discussionmentioning

confidence: 99%

From parts to whole: Embracing systems science in community psychology

Lawlor,

Metta

2023

American J of Comm Psychol

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With our field's strong focus on context for understanding and acting on social problems, community psychologists have frequently elevated the importance of employing systems thinking and methods that help us to understand systems more effectively. As a result, community psychologists have adopted some methods from the interdisciplinary field of systems science. In this virtual special issue, we will compare how several of these approaches have been used in publications in the AJCP in the last 50 years. We identify differences in their popularity, implementation with communities, and how they create generative discussion in the field. We conclude by looking to the future to explore ways community psychology can deepen engagement with methods from systems science.

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Section: Discussionmentioning

confidence: 99%

From parts to whole: Embracing systems science in community psychology

Lawlor,

Metta

2023

American J of Comm Psychol

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“…Agent-based modeling is a scientific research method based on computer models that simulate the behavior and interactions of autonomous agents in a complex system [16]. Agent-based models represent the system as a collection of individual agents, each with its own unique characteristics, rules, and behaviors.…”

Section: Agent-based Modelingmentioning

confidence: 99%

Market Impact Analysis of Financial Literacy among A-Share Market Investors: An Agent-Based Model

Zhou,

Xiong,

Llacay

et al. 2023

Entropy

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Financial literacy has become increasingly crucial in today’s complex financial markets. This paper explores the impact of financial literacy on the stock market by establishing an artificial financial market that aligns with the characteristics of the Chinese A-share market using agent-based modeling. The study incorporates financial literacy into investors’ mixed beliefs and simulates their behavior in the market. The results show that improving individual investors’ financial literacy can improve market quality and investor performance, as well as reduce the unequal distribution of wealth to some extent. However, the phenomenon of speculative trading and irrational behavior in the market can pose potential risks that require regulatory measures. Thus, policy recommendations to improve individual investors’ financial literacy and establish corresponding regulatory measures are proposed.

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“…Despite their potential complexity, games not only offer the opportunity to simulate what-if scenarios about possible automated decisions regarding in social provision, but also provide the potential to engage the wider public in discussions surrounding AI and social service provision [5,6]. Increased public understanding and input contribute to a more democratic and transparent approach to AI development and the use of concepts as ethnicity [7] and transparency [8] in decision-making models in virtual environments before implementing them in real-world scenarios allows for identifying potential flaws and biases, minimizing the risk of harmful consequences in actual social service provision.…”

Section: Introductionmentioning

confidence: 99%

Sequence Pattern Mining for Citizens Behaviour Learning in Fair-Purpose Social Games. Some Preliminary Results

López,

Campdepadros,

Sabater

2023

Frontiers in Artificial Intelligence and Applications

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Artificial Intelligence can be used to understand how citizens interact in a society with the aim to work together towards a better world. The application of AI in this domain has shown immense potential, particularly in leveraging games as powerful tools to simulate individual roles within a society. This research endeavors to explore how sequence pattern mining are applied to data coming from a game, in which humans are posed with the dilemma of progressing through their jobs, while enjoying life, trying to catch an equilibrium between happiness and healthiness. Preliminary results on a game played with 13 citizens shows the feasibility of sequence learning for this purpose. Our findings shed light on the intricate interplay of individual aspirations, communal synergies, and the pursuit of equilibrium, laying the foundation for future advancements in AI-driven methodologies for sociological investigations.

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The Ethics of Agent-Based Social Simulation

Cited by 6 publications

References 70 publications

From parts to whole: Embracing systems science in community psychology

From parts to whole: Embracing systems science in community psychology

Market Impact Analysis of Financial Literacy among A-Share Market Investors: An Agent-Based Model

Sequence Pattern Mining for Citizens Behaviour Learning in Fair-Purpose Social Games. Some Preliminary Results

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