The model represents a team intended at designing a methodology for Institutional Planning. Included in ICAART’14 to exemplify how emotions can be identified in SocLab; and in ESSA’14 to show the Efficiency of Organizational Withdrawal vs Commitment.

ThomondSim is a simulation of the political and economic landscape of the medieval kingdom of Thomond, southwestern Ireland, between 1276 and 1318.

Its goal is to analyze how deteriorating environmental and economic conditions caused by the Little Ice Age (LIA), the Great European Famine of 1315-1322, and wars between England and Scotland affected the outcomes of a local war involving Gaelic and English aristocratic lineages.
This ABM attempts to model both the effects of devastation on the human environment and the modus operandi of late-medieval war and diplomacy.

The model is the digital counterpart of the science discovery board game The Triumphs of Turlough. Its procedures closely correspond to the game’s mechanics, to the point that ToT can be considered an interactive, analog version of this ABM.

This is a gender differentiation model in terms of reputations, prestige and self-esteem (presented in the paper https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236840). The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017) considering two groups.

This agent-based model studies how inequalities can be explained by the difference of open-mindness between two groups of interacting agents. We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters. We study an heterogeneous population of two different groups: one more open to influence of others, taking less into account their perceived difference of esteem, called L; a second one less prone to it, called S, who designed the credibility they give to others strongly based on how higher or lower valued than themselves they perceive them.

We show that a mixed population always turns in favor to some agents belonging to the group of less open-minded agents S, and harms the other group: (1) the average group self-opinion or reputation of S is always better than the one of L; (2) the higher rank in terms of reputation are more frequently occupied by the S agents while the L agents occupy more the bottom rank; (3) the properties of the dynamics of differentiation between the two groups are similar to the properties of the glass ceiling effect proposed by Cotter et al (2001).

The Communication-Based Model of Perceived Descriptive Norm Dynamics in Digital Networks (COMM-PDND) is an agent-based model specifically created to examine the dynamics of perceived descriptive norms in the context of digital network structures. The model, developed as part of a master’s thesis titled “The Dynamics of Perceived Descriptive Norms in Digital Network Publics: An Agent-Based Simulation,” emphasizes the critical role of communication processes in norm formation. It focuses on the role of communicative interactions in shaping perceived descriptive norms.

The COMM-PDND is tuned to explore the effects of normative deviance in digital social networks. It provides functionalities for manipulating agents according to their network position, and has a versatile set of customizable parameters, making it adaptable to a wide range of research contexts.

This model is an agent-based simulation written in Python 2.7, which simulates the cost of social care in an ageing UK population. The simulation incorporates processes of population change which affect the demand for and supply of social care, including health status, partnership formation, fertility and mortality. Fertility and mortality rates are drawn from UK population data, then projected forward to 2050 using the methods developed by Lee and Carter 1992.

The model demonstrates that rising life expectancy combined with lower birthrates leads to growing social care costs across the population. More surprisingly, the model shows that the oft-proposed intervention of raising the retirement age has limited utility; some reductions in costs are attained initially, but these reductions taper off beyond age 70. Subsequent work has enhanced and extended this model by adding more detail to agent behaviours and familial relationships.

The version of the model provided here produces outputs in a format compatible with the GEM-SA uncertainty quantification software by Kennedy and O’Hagan. This allows sensitivity analyses to be performed using Gaussian Process Emulation.

This is a replication of the SequiaBasalto model, originally built in Cormas by Dieguez Cameroni et al. (2012, 2014, Bommel et al. 2014 and Morales et al. 2015). The model aimed to test various adaptations of livestock producers to the drought phenomenon provoked by climate change. For that purpose, it simulates the behavior of one livestock farm in the Basaltic Region of Uruguay. The model incorporates the price of livestock, fodder and paddocks, as well as the growth of grass as a function of climate and seasons (environmental submodel), the life cycle of animals feeding on the pasture (livestock submodel), and the different strategies used by farmers to manage their livestock (management submodel). The purpose of the model is to analyze to what degree the common management practices used by farmers (i.e., proactive and reactive) to cope with seasonal and interannual climate variations allow to maintain a sustainable livestock production without depleting the natural resources (i.e., pasture). Here, we replicate the environmental and livestock submodel using NetLogo.

One year is 368 days. Seasons change every 92 days. Each day begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of cows according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. After consumption, cows grow and reproduce, and a new grass height is calculated. Cows then move to the patch with less cows and with the highest grass height. This updated grass height value will be the initial grass height for the next day.

AncientS-ABM is an agent-based model for simulating and evaluating the potential social organization of an artificial past society, configured by available archaeological data. Unlike most existing agent-based models used in archaeology, our ABM framework includes completely autonomous, utility-based agents. It also incorporates different social organization paradigms, different decision-making processes, and also different cultivation technologies used in ancient societies. Equipped with such paradigms, the model allows us to explore the transition from a simple to a more complex society by focusing on the historical social dynamics; and to assess the influence of social organization on agents’ population growth, agent community numbers, sizes and distribution.

AncientS-ABM also blends ideas from evolutionary game theory with multi-agent systems’ self-organization. We model the evolution of social behaviours in a population of strategically interacting agents in repeated games where they exchange resources (utility) with others. The results of the games contribute to both the continuous re-organization of the social structure, and the progressive adoption of the most successful agent strategies. Agent population is not fixed, but fluctuates over time, while agents in stage games also receive non-static payoffs, in contrast to most games studied in the literature. To tackle this, we defined a novel formulation of the evolutionary dynamics via assessing agents’ rather than strategies’ fitness.

As a case study, we employ AncientS-ABM to evaluate the impact of the implemented social organization paradigms on an artificial Bronze Age “Minoan” society, located at different geographical parts of the island of Crete, Greece. Model parameter choices are based on archaeological evidence and studies, but are not biased towards any specific assumption. Results over a number of different simulation scenarios demonstrate better sustainability for settlements consisting of and adopting a socio-economic organization model based on self-organization, where a “heterarchical” social structure emerges. Results also demonstrate that successful agent societies adopt an evolutionary approach where cooperation is an emergent strategic behaviour. In simulation scenarios where the natural disaster module was enabled, we observe noticeable changes in the settlements’ distribution, relating to significantly higher migration rates immediately after the modeled Theran eruption. In addition, the initially cooperative behaviour is transformed to a non-cooperative one, thus providing support for archaeological theories suggesting that the volcanic eruption led to a clear breakdown of the Minoan socio-economic system.

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The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017). We aim at better explaining some patterns generated by this model, using a derived mathematical approximation of the evolution of the opinions averaged.

We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other, and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters.

We show that the inequality of reputations among agents have a negative effect on the opinions about the agents of low status.The mathematical analysis of the opinion dynamic shows that the lower the status of the agent, the more detrimental the interactions are for the opinions about this agent, especially when gossip is activated, while the interactions always tend to increase the opinions about agents of high status.

The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017) with the addition of group idenetity. We aim at better explaining some patterns generated by this model, using a derived mathematical approximation of the evolution of the opinions averaged.

We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other, and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters. Moreover, each agent belongs to a single group and the opinions within the group are attracted to their average.

We show that a group hierarchy can emerges from this model, and that the inequality of reputations among groups have a negative effect on the opinions about the groups of low status. The mathematical analysis of the opinion dynamic shows that the lower the status of the group, the more detrimental the interactions with the agents of other groups are for the opinions about this group, especially when gossip is activated. However, the interactions between agents of the same group tend to have a positive effect on the opinions about this group.

The purpose of the model is to better understand, how different factors for human residential choices affect the city’s segregation pattern. Therefore, a Schelling (1971) model was extended to include ethnicity, income, and affordability and applied to the city of Salzburg. So far, only a few studies have tried to explore the effect of multiple factors on the residential pattern (Sahasranaman & Jensen, 2016, 2018; Yin, 2009). Thereby, models using multiple factors can produce more realistic results (Benenson et al., 2002). This model and the corresponding thesis aim to fill that gap.