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26 articles matched your search for the keywords:
Multi-Agent Simulation, Leadership, Violence, Warfare, Pacific Island Societies

Kinship Based Demographic Simulation of Societal Processes

Dwight Read
Journal of Artificial Societies and Social Simulation 1 (1) 1

Kyeywords: Multi-Agent Simulation, Cultural Knowledge, Hunting and Gathering Societies
Abstract: The social boundaries of small scale human societies are defined through culturally defined kin relations that transcend the specifics of the genealogical relationships produced through procreation. Kinship knowledge is culturally defined, distributed knowledge that provides structure for the persons produced through demographic processes. However, the interplay between the demographic system and the cultural system has been difficult to model. Genealogical data are static and do not show how the vagaries of demographic processes affect implementation of a culturally defined, conceptual system. Demographic simulations can provide the dynamic dimension, but usually lack information on how the changing demographic makeup of a population affects application of culturally defined rules relating to marriage, reproduction, residence and the like. This paper presents results obtained from implementation of a multi-agent, demographically driven, simulation of a hunting and gathering group in which each agent is imbued with cultural knowledge that affects decisions to be made about marriage, reproduction and place of residence. The goal is to assess the implications of demographic processes, ego-centered decision making, and culturally determined structures (kin relations, social groupings and the like) for the resulting social system. Questions addressed in the simulation are based on ethnographic observations and it is shown that the simulation provides an effective means to assess the validity of hypotheses about the ethnographic observations.

Simulation of Order Fulfillment in Divergent Assembly Supply Chains

Troy J Strader, Fu-ren Lin and Michael J Shaw
Journal of Artificial Societies and Social Simulation 1 (2) 5

Kyeywords: Supply Chain Management, Multi-Agent Simulation, Swarm, Decision Support Systems, Electronic Commerce, Computer Industry, Electronics Industry
Abstract: Management of supply chains is a difficult task involving coordination and decision-making across organizational boundaries. Computational modeling using multi-agent simulation is a tool that can provide decision support for supply chain managers. We identify the components of a supply chain model and implement it in the Swarm multi-agent simulation platform. The model is used to study the impact of information sharing on order fulfillment in divergent assembly supply chains (commonly associated with the computer and electronics industries). We find that efficient information sharing enables inventory costs to be reduced while maintaining acceptable order fulfillment cycle times. This is true because information, which provides the basis for enhanced coordination and reduced uncertainty, can substitute for inventory.

Violence and Revenge in Egalitarian Societies

Stephen Younger
Journal of Artificial Societies and Social Simulation 8 (4) 11

Kyeywords: Violence, Revenge, Egalitarian Culture, Homicide, Population Density, Tolerance, Food Supply
Abstract: Discrete agent simulation was used to investigate the role of violence and revenge in model egalitarian societies. A population of 100 agents inhabited a landscape of 20x20 squares containing five sources of food. Agents moved about the landscape in search of food, shared, stole, mated, produced offspring, and ultimately died of old age. Violence and revenge reduced the survival probability of the population and, for surviving populations, replaced hunger as the second leading cause of death after old age. Excluding large segments of the population from violence and revenge significantly improved survival rates. Tolerance to transgressions reduced the number of agents killed in revenge attacks. Higher population density increased the number of revenge deaths but also increased the survival rate of the total population. Decreasing the food supply for a fixed initial population resulted in more deaths due to violence and revenge. Flight from known aggressors enhanced the survival of the total population, at the expense of social cohesion. When killing had a positive social value the survival rate of the total population increased as the number of revenge killings decreased. These results are discussed in the context of ethnographic observations of a number of egalitarian societies.

Multi-Agent Simulation of Emergence of Schwa Deletion Pattern in Hindi

Monojit Choudhury, Anupam Basu and Sudeshna Sarkar
Journal of Artificial Societies and Social Simulation 9 (2) 2

Kyeywords: Language Change, Linguistic Agent, Language Game, Multi-Agent Simulation, Schwa Deletion
Abstract: Recently, there has been a revival of interest in multi-agent simulation techniques for exploring the nature of language change. However, a lack of appropriate validation of simulation experiments against real language data often calls into question the general applicability of these methods in modeling realistic language change. We try to address this issue here by making an attempt to model the phenomenon of schwa deletion in Hindi through a multi-agent simulation framework. The pattern of Hindi schwa deletion and its diachronic nature are well studied, not only out of general linguistic inquiry, but also to facilitate Hindi grapheme-to-phoneme conversion, which is a preprocessing step to text-to-speech synthesis. We show that under certain conditions, the schwa deletion pattern observed in modern Hindi emerges in the system from an initial state of no deletion. The simulation framework described in this work can be extended to model other phonological changes as well.

Votes and Lobbying in the European Decision-Making Process: Application to the European Regulation on GMO Release

Juliette Rouchier and Sophie Thoyer
Journal of Artificial Societies and Social Simulation 9 (3) 1

Kyeywords: Lobbying, Europe, GMO, Multi-Agent Simulation, Public Choice, Politician, Voter, Group Contest
Abstract: The paper presents a multi-agent model simulating a two-level public decision game in which politicians, voters and interest groups interact. The objective is to model the political market for influence at the domestic level and at the international level, and to assess how new consultation procedures affect the final decision. It is based on public choice theory as well as on political science findings. We consider in this paper that lobbying groups have different strategies for influencing voters and decision-makers, with long-term and short-term effects. Our computational model enables us to represent the situation as an iterative process, in which past decisions have an impact on the preferences and choices of agents in the following period. In the paper, the model is applied to the European decision-making procedure for authorizing the placing on the market of Genetically Modified Organisms (GMO). It illustrates the political links between public opinions, lobbying groups and elected representatives at the national scale in the 15 country members, and at the European scale. It compares the procedure which was defined by the European 1990/220 Directive in 1990 with the new procedure, the 2001/18 Directive, which replaced it in 2001. The objective is to explore the impact of the new decision rules and the reinforced public participation procedures planned by the 2001/18 Directive on the lobbying efficiency of NGOs and biotechnology firms, and on the overall acceptability of the European decision concerning the release of new GMOs on the European territory.

Higher-Order Simulations: Strategic Investment Under Model-Induced Price Patterns

Gilbert Peffer and Barbara Llacay
Journal of Artificial Societies and Social Simulation 10 (2) 6

Kyeywords: Financial Markets, Multi-Agent Simulation, Performativity, Higher-Order Strategies
Abstract: The trading and investment decision processes in financial markets become ever more dependent on the use of valuation and risk models. In the case of risk management for instance, modelling practice has become quite homogeneous and the question arises as to the effect this has on the price formation process. Furthermore, sophisticated investors who have private information about the use and characteristics of these models might be able to make superior gains in such an environment. The aim of this article is to test this hypothesis in a stylised market, where a strategic investor trades on information about the valuation and risk management models used by other market participants. Simulation results show that under certain market conditions, such a \'higher-order\' strategy generates higher profits than standard fundamental and momentum strategies that do not draw on information about model use.

Social Simulation of Stock Markets: Taking It to the Next Level

Arvid Oskar Ivar Hoffmann, Wander Jager and J. H. Von Eije
Journal of Artificial Societies and Social Simulation 10 (2) 7

Kyeywords: Agent-Based Computational Finance, Artificial Stock Markets, Behavioral Finance, Micro-Macro Links, Multi-Agent Simulation, Stock Market Characteristics
Abstract: This paper studies the use of social simulation in linking micro level investor behaviour and macro level stock market dynamics. Empirical data from a survey on individual investors\' decision-making and social interaction was used to formalize the trading and interaction rules of the agents of the artificial stock market SimStockExchange. Multiple simulation runs were performed with this artificial stock market, which generated macro level results, like stock market prices and returns over time. These outcomes were subsequently compared to empirical macro level data from real stock markets. Partial qualitative as well as quantitative agreement between the simulated asset returns distributions and the asset returns distributions of the real stock markets was found.

Research on Multi-Agent Simulation of Epidemic News Spread Characteristics

Xiaoguang Gong and Renbin Xiao
Journal of Artificial Societies and Social Simulation 10 (3) 1

Kyeywords: Multi-Agent Simulation, News Spread, Small World Network , Epidemic
Abstract: The spread of news about an epidemic can easily lead to a social panic. In order to devise measures to control such a panic, it is necessary to consider characteristics of the spread of epidemic news, based on mechanisms at the individual level. In this paper, first, some features of multi-agent simulation are reviewed. Then a multi-agent simulation model of epidemic news spread (ENS) is designed and realized. Based on simulation experiments and sensitivity analyses, the influence of social relationships, the degree of trust in news of the epidemic, the epidemic spread intensity and the network structure of the epidemic news spread are studied. The research results include: (1) As the number of social relationships increases, the rate of spread of epidemic news rapidly rises, and the ratio of people who have heard the news directly decreases. The result is that the \'radiation effect\' of the epidemic news spread will be enhanced when the number of social relationships increases. (2) With the increase of the degree of trust in the news, the rate of spread of the news will also rapidly increase, but variation in the ratio of the people who have heard the news directly is not significant. This means that the \'radiation effect\' of the spread of the news does not change much more in relation to the degree of trust in the epidemic news. (3) The ratio of the people who have heard the news directly increases when the infection range increases (i.e. the spread intensity of epidemic increases), and vice versa. But the variation of the speed of the epidemic news spread is not significant. (4) When the network structure is assumed to be a small world network, the spread speed will be slower than that in a random network with the same average vertex degree and the forgetting speed will be faster than that in a random network with the same average vertex degree.

Socio-Economic Mechanisms to Coordinate the Internet of Services: The Simulation Environment SimIS

Stefan König, Sebastian Hudert and Torsten Eymann
Journal of Artificial Societies and Social Simulation 13 (2) 6

Kyeywords: Multi-Agent Simulation, Internet, Simulation Tools
Abstract: Visions of 21st century information systems show highly specialized digital services and resources, which interact continuously and with a global reach. Especially with the emergence of technologies, such as the semantic web or software agents, intelligent services within these settings can be implemented, automatically communicating and negotiating over the Internet about digital resources without human intervention. Such environments will eventually realize the vision of an open and global Internet of Services (IoS). In this paper we present an agent-based simulation model and toolkit for the IoS: 'SimIS - Simulating an Internet of Services'. Employing SimIS, distributed management mechanisms and protocols can be investigated in a simulated IoS environment before their actual deployment.

Flocking Behaviour: Agent-Based Simulation and Hierarchical Leadership

Vicenç Quera, Francesc S. Beltran and Ruth Dolado
Journal of Artificial Societies and Social Simulation 13 (2) 8

Kyeywords: Flocking Behaviour; Hierarchical Leadership; Agent-Based Simulation; Social Dynamics
Abstract: We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Leadership in Small Societies

Stephen Younger
Journal of Artificial Societies and Social Simulation 13 (3) 5

Kyeywords: Leadership, Reciprocity, Pacific Island Societies, Norms
Abstract: Multi-agent simulation was used to study several styles of leadership in small societies. Populations of 50 and100 agents inhabited a bounded landscape containing a fixed number of food sources. Agents moved about the landscape in search of food, mated, produced offspring, and died either of hunger or at a predetermined maximum age. Leadership models focused on the collection and redistribution of food. The simulations suggest that individual households were more effective at meeting their needs than a simple collection-redistribution scheme. Leadership affected the normative makeup of the population: altruistic leaders caused altruistic societies and demanding leaders caused aggressive societies. Specific leadership styles did not provide a clear advantage when two groups competed for the same resources. The simulation results are compared to ethnographic observations of leadership in Pacific island societies.

Scale-Free Relationships Facilitate Cooperation in Spatial Games with Sequential Strategy

Tetsushi Ohdaira and Takao Terano
Journal of Artificial Societies and Social Simulation 14 (3) 3

Kyeywords: Cooperation, Second-Best Decision, Multi-Agent Simulation, Spatial Game, Collusive Tendering
Abstract: Recently, the area of study of spatial game continuously has extended, and researchers have especially presented a lot of works of coevolutionary mechanism. We have recognized coevolutionary mechanism as one of the factors for the promotion of cooperation like five rules by Nowak. However, those studies still deal with the optimal response (best decision). The best decision is persuasive in most cases, but does not apply to all situations in the real world. Contemplating that question, researchers have presented some works discussing not only the best decision but also the second-best decision. Those studies compare the results between the best and the second-best, and also state the applicability of the second-best decision. This study, considering that trend, has extended the match between two groups to spatial game with the second-best decision. This extended model expresses relationships of groups as a spatial network, and every group matches other groups of relationships. Then, we examine how mutual cooperation changes in each case where either we add probabilistic perturbation to relationships or ties form various types of the structure. As a result, unlike most results utilizing the best decision, probabilistic perturbation does not induce any change. On the other hand, when ties are the scale-free structure, mutual cooperation is enhanced like the case of the best decision. When we probe the evolution of strategies in that case, groups with many ties play a role for leading the direction of decision as a whole. This role appears without explicit assignment. In the discussion, we also state that the presented model has an analogy to the real situation, collusive tendering.

Leadership, Violence, and Warfare in Small Societies

Stephen Younger
Journal of Artificial Societies and Social Simulation 14 (3) 8

Kyeywords: Multi-Agent Simulation, Leadership, Violence, Warfare, Pacific Island Societies
Abstract: Multi-agent simulation was used to study the effect of simple models of leadership on interpersonal violence and warfare in small societies. Agents occupied a two dimensional landscape containing villages and food sources. Sharing and stealing contributed to normative reputation. Violence occurred during theft, in revenge killings, and in leader-directed warfare between groups. The simulations were run over many generations to examine the effect of violence on social development. The results indicate that leadership reduced the survival probability of the population. Interpersonal violence killed more agents than warfare when intra-group violence was permitted. More aggressive leaders did not always prevail over less aggressive leaders due to the inherent risks associated with attacks. The results of the simulation are compared to cross-cultural studies and to observations of indigenous Pacific island societies.

Outstanding in the Field: Evaluating Auction Markets for Farmland Using Multi-Agent Simulation

Adam Arsenault, James Nolan, Richard Schoney and Donald Gilchrist
Journal of Artificial Societies and Social Simulation 15 (1) 11

Kyeywords: Multi-Agent Simulation, Auctions, Agriculture
Abstract: Land acquisition and ownership is an important part of modern agriculture in North America. Given the unique nature of farmland as a good, this paper develops a multi-agent simulation of farmland auction markets in a Canadian context. The model is used to generate data on land transactions between farm agents to determine if a particular auction design or type is better suited to farmland transactions. The simulation uses three different sealed-bid auctions, as well as an English auction. The auctions are compared on the basis of efficiency, stability, and perceived surplus. We find that the form of agent learning about land markets affects both sale price and the variance of sale prices in all of the studied auctions. The second-price-sealed-bid auction generates the most perceived surplus, most equitable share of surplus, and also decreases uncertainty in the common-value element of prices. But on a macroscopic level, it appears that auction choice does not influence market structure or evolution over time.

Nonlinear Dynamics of Crime and Violence in Urban Settings

Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic, Jadranka Mezic and P. Jeffrey Brantingham
Journal of Artificial Societies and Social Simulation 15 (1) 2

Kyeywords: Agent-Based Modeling, Crime, Violence, Anthropology, Socio-Cultural Model, Police
Abstract: We perform analysis of data on crime and violence for 5,660 U.S. cities over the period of 2005-2009 and uncover the following trends: 1) The proportion of law enforcement officers required to maintain a steady low level of criminal activity increases with the size of the population of the city; 2) The number of criminal/violent events per 1,000 inhabitants of a city shows non-monotonic behavior with size of the population. We construct a dynamical model allowing for system-level, mechanistic understanding of these trends. In our model the level of rational behavior of individuals in the population is encoded into each citizen's perceived risk function. We find strong dependence on size of the population, which leads to partially irrational behavior on the part of citizens. The nature of violence changes from global outbursts of criminal/violent activity in small cities to spatio-temporally distributed, decentralized outbursts of activity in large cities, indicating that in order to maintain peace, bigger cities need larger ratio of law enforcement officers than smaller cities. We also observe existence of tipping points for communities of all sizes in the model: reducing the number of law enforcement officers below a critical level can rapidly increase the incidence of criminal/violent activity. Though surprising, these trends are in agreement with the data.

Validation of an Agricultural MAS for Southland, New Zealand

Bill Kaye-Blake, Chris Schilling and Elizabeth Post
Journal of Artificial Societies and Social Simulation 17 (4) 5

Kyeywords: Agriculture, Interdisciplinary Research, Multi-Agent Simulation, Validation, Agent-Based Model
Abstract: This paper describes the process and results of validating a simulation model of agriculture for a region in New Zealand. Validation is treated as a process, in which simulation models are made useful for specific purposes by making them conform to observed historical trends and relationships. In this case, the model was calibrated to reproduce the year-by-year conversion to dairying from 1993 to 2012 in Southland, New Zealand. This was achieved by holding constant some elements of the simulation model, based on economic theory or data, and by running simulations on a range of values for two key parameters. The paper describes the model and process, and demonstrates that empirical validation is possible if approached pragmatically with a view to the intended use of the model. Important elements are: using stylised facts to limit the parameter space ex ante, establishing the range of model outcomes and focusing on the most likely parameter space, focusing the search for parameter values where there is the greatest uncertainty, and using historical data to calibrate models.

Impacts of Farmer Coordination Decisions on Food Supply Chain Structure

Caroline Krejci and Benita Beamon
Journal of Artificial Societies and Social Simulation 18 (2) 19

Kyeywords: Food Supply Chains, Sustainable Agriculture, Coordination, Agent-Based Modeling, Farmer Decision Making, Multi-Agent Simulation
Abstract: To increase profitability, farmers often decide to form strategic partnerships with other farmers, pooling their resources and outputs for greater efficiency and scale. These coordination decisions can have far-reaching and complex implications for overall food supply chain structural emergence, which in turn impacts system outcomes and long-term sustainability. In this paper, we describe an agent-based model that explores the impacts of farmer coordination decisions on the development of food supply chain structure over time. This model focuses on one type of coordination mechanism implementation method, in which coordinated farmer groups produce a single crop type and combine their yields to achieve economies of scale. The farmer agents’ decisions to coordinate with one another depend on their evaluation of the tradeoff between their autonomy and the expected economic benefits of coordination. Each coordination decision is a bilateral process in which the terms of group reward sharing are negotiated. We capture the effects of farmers’ size, income, and autonomy premia, as well as volume-price relationships and group profit-sharing rules, on the rate of farmer coordination and the number and size of groups that form. Results indicate that under many conditions, coordination groups tend to consolidate over time, which suggests implications for overall supply chain structural resilience.

Simulation of Technology Sourcing Overseas Post-Merger Behaviors in a Global Game Model

Feiqiong Chen, Qiaoshuang Meng and Fei Li
Journal of Artificial Societies and Social Simulation 19 (4) 13

Kyeywords: Post-Merger Integration, Technology Innovation, Multi-Agent Simulation, Integration Degree, Target Autonomy
Abstract: The abilities to efficiently identify potential innovation profits and form an optimal post-merger strategy are key to evaluating overseas merger and acquisition (M&A) performances. The paper uses a global game with asymmetric payoff structure and multi-agent simulation methods to analyze the optimal overseas post-merger strategy. We model three stages of the M&A processes: merger decision stage, post-merger integration stage, and technology innovation after M&A, to analyze how different resource similarity and resource complementarity of the two companies influence the degree of optimal post-merger integration and target autonomy as well as technology innovation profit after M&A. The agent-based simulation shows that, in overseas M&As, resource similarity has a positive relation with integration and a negative relation with target autonomy; however, resource complementarity has the opposite effect. The negative interaction effect between resource similarity and complementarity will decrease the degrees of integration. In high-resource-similarity and low-resource-complementarity M&As, a high integration degree and low target autonomy will maximize innovation profit, while for high-resource-similarity and high-resource-complementarity M&As, a high integration degree and target autonomy is best for innovation profit. For low-resource-similarity and high-resource-complementarity M&As, a low integration degree and high target autonomy will be the best post-merger strategy. Model outputs are robust to variations of the parameters.

Comparing Prediction Market Mechanisms: An Experiment-Based and Micro Validated Multi-Agent Simulation

Frank M. A. Klingert and Matthias Meyer
Journal of Artificial Societies and Social Simulation 21 (1) 7

Kyeywords: Continuous Double Auction, Logarithmic Market Scoring Rule, Market Mechanisms, Multi-Agent Simulation, Prediction Markets, Simulation Validation
Abstract: Prediction markets are a promising instrument for drawing on the “wisdom of the crowds”. For instance, in a corporate context they have been used successfully to forecast sales or project risks by tapping into the heterogeneous information of decentralized actors in and outside of companies. Among the main market mechanisms implemented so far in prediction markets are (1) the continuous double auction and (2) the logarithmic market scoring rule. However, it is not fully understood how this choice affects crucial variables like prediction market accuracy or price variation. Our paper uses an experiment-based and micro validated simulation model to improve the understanding of the mechanism-related effects and to inform further laboratory experiments. The results underline the impact of mechanism selection. Due to the higher number of trades and the lower standard deviation of the price, the logarithmic market scoring rule seems to have a clear advantage at a first glance. This changes when the accuracy level, which is the most important criterion from a practical perspective, is used as an independent variable; the effects become less straightforward and depend on the environment and actors. Besides these contributions, this work provides an example of how experimental data can be used to validate agent strategies on the micro level using statistical methods.

A Generative Model of the Mutual Escalation of Anxiety Between Religious Groups

F. LeRon Shults, Ross Gore, Wesley J. Wildman, Christopher Lynch, Justin E. Lane and Monica Toft
Journal of Artificial Societies and Social Simulation 21 (4) 7

Kyeywords: Agent-Based Model, Religious Violence, Identity Fusion, Social Identity, Terror Management, Xenophobia
Abstract: We propose a generative agent-based model of the emergence and escalation of xenophobic anxiety in which individuals from two different religious groups encounter various hazards within an artificial society. The architecture of the model is informed by several empirically validated theories about the role of religion in intergroup conflict. Our results identify some of the conditions and mechanisms that engender the intensification of anxiety within and between religious groups. We define mutually escalating xenophobic anxiety as the increase of the average level of anxiety of the agents in both groups over time. Trace validation techniques show that the most common conditions under which longer periods of mutually escalating xenophobic anxiety occur are those in which the difference in the size of the groups is not too large and the agents experience social and contagion hazards at a level of intensity that meets or exceeds their thresholds for those hazards. Under these conditions agents will encounter out-group members more regularly, and perceive them as threats, generating mutually escalating xenophobic anxiety. The model’s capacity to grow the macro-level emergence of this phenomenon from micro-level agent behaviors and interactions provides the foundation for future work in this domain.

Conflicts Induced by Different Responses to Land Expropriation Among the Farmers Involved During Urbanization in China

Haijun Bao, Xiaohe Wu, Haowen Wang, Qiuxiang Li, Yi Peng and Shibao Lu
Journal of Artificial Societies and Social Simulation 22 (1) 7

Kyeywords: Conflict of Interests, Land Expropriation, Evolutionary Game, Multi-Agent Simulation, Farmers
Abstract: Expropriation of collectively-owned land has become an important realistic path for achieving urban development and new urbanization in China considering the shortage of state-owned land. During this process, farmers involved in land expropriation are often in conflict with one another because of the asymmetry of their interests. Such conflicts have a considerable effect on social harmony and stability. However, few studies have investigated such conflict of interests between farmers. Therefore, this research analyzed game behavior for the conflict of interests among farmers. A two-dimensional symmetric evolutionary game model and a multi-agent simulation experiment were used to explore the conflicts induced by the farmers’ different responses to land expropriation. This research finds that the changing strategy choices of farmers in the evolutionary game on collectively owned land expropriation are the main reasons for the occurrence of villager’ confrontations and “nail households”. Results provide targeted policy recommendations for local governments to promote cooperation among farmers, thereby enhancing social harmony. The findings also serve as references for other countries and regions in dealing with intra-conflict of interests in land expropriation.

The Evolution of Tribalism: A Social-Ecological Model of Cooperation and Inter-Group Conflict Under Pastoralism

Nicholas Seltzer
Journal of Artificial Societies and Social Simulation 22 (2) 6

Kyeywords: Evolution, Cooperation, Inter-Group, Conflict, Warfare, Tribal
Abstract: This study investigates a possible nexus between inter-group competition and intra-group cooperation, which may be called "tribalism." Building upon previous studies demonstrating a relationship between the environment and social relations, the present research incorporates a social-ecological model as a mediating factor connecting both individuals and communities to the environment. Cyclical and non-cyclical fluctuation in a simple, two-resource ecology drive agents to adopt either "go-it-alone" or group-based survival strategies via evolutionary selection. Novelly, this simulation employs a multilevel selection model allowing group-level dynamics to exert downward selective pressures on individuals' propensity to cooperate within groups. Results suggest that cooperation and inter-group conflict are co-evolved in a triadic relationship with the environment. Resource scarcity increases inter-group competition, especially when resources are clustered as opposed to widely distributed. Moreover, the tactical advantage of cooperation in the securing of clustered resources enhanced selective pressure on cooperation, even if that implies increased individual mortality for the most altruistic warriors. Troubling, these results suggest that extreme weather, possibly as a result of climate change, could exacerbate conflict in sensitive, weather-dependent social-ecologies---especially places like the Horn of Africa where ecologically sensitive economic modalities overlap with high-levels of diversity and the wide-availability of small arms. As well, global development and foreign aid strategists should consider how plans may increase the value of particular locations where community resources are built or aid is distributed, potentially instigating tribal conflict. In sum, these factors, interacting with pre-existing social dynamics dynamics, may heighten inter-ethnic or tribal conflict in pluralistic but otherwise peaceful communities.

Comparing Actual and Simulated HFT Traders' Behavior for Agent Design

Masanori Hirano, Kiyoshi Izumi, Hiroyasu Matsushima and Hiroki Sakaji
Journal of Artificial Societies and Social Simulation 23 (3) 6

Kyeywords: Artificial Market, Multi-Agent Simulation, Data-Mining, High-Frequency Trade, Market-Making, Clustering
Abstract: Recently financial markets have shown significant risks and levels of volatility. Understanding the sources of these risks require simulation models capable of representing adequately the real mechanisms of markets. In this paper, we compared data of the high-frequency-trader market-making (HFT-MM) strategy from both the real financial market and our simulation. Regarding the former, we extracted trader clusters and identified one cluster whose statistical indexes indicated HFT-MM features. We then analyzed the difference between these traders' orders and the market price. In our simulation, we built an artificial market model with a continuous double auction system, stylized trader agents, and HFT-MM trader agents based on prior research. As an experiment, we compared the distribution of the order placements of HFT-MM traders in the real and simulated financial data. We found that the order placement distribution near the market or best price in both the real data and the simulations were similar. However, the orders far from the market or best price differed significantly when the real data exhibited a wider range of orders. This indicates that in order to build more realistic simulation of financial markets, integrating fine-grained data is essential.

The Unknown of the Pandemic: An Agent-Based Model of Final Phase Risks

Marco Cremonini and Samira Maghool
Journal of Artificial Societies and Social Simulation 23 (4) 8

Kyeywords: Stochastic Epidemic Model, Multi-Agent Simulation, Network Analysis, Agent-Based Model, Risk Analysis
Abstract: Lifting social restrictions is one of the most critical decisions that public health authorities have to face during a pandemic such as COVID-19. This work focuses on the risk associated with such a decision. We have called the period from the re-opening decision to epidemic expiration the ’final epidemic phase’, and considered the critical epidemic conditions which could possibly emerge in this phase. The factors we have considered include: the proportion of asymptomatic cases, a mitigation strategy based on testing and the average duration of infectious states. By assuming hypothetical configurations at the time of the re-opening decision and the partial knowledge concerning epidemic dynamics available to public health authorities, we have analyzed the risk of the re-opening decision based on possibly unreliable estimates. We have presented a discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations. Our results show the different outcomes produced by different proportions of undetected asymptomatic cases, different probabilities of asymptomatic cases detected and contained, and a multivariate analysis of risk based on the average duration of asymptomatic and contained states. Finally, our analysis highlights that enduring uncertainty, typical of this pandemic, requires a risk analysis approach to complement epidemiological studies.

VIDA: A Simulation Model of Domestic Violence in Times of Social Distancing

Lígia Mori Madeira, Bernardo Alves Furtado and Alan Dill
Journal of Artificial Societies and Social Simulation 24 (4) 1

Kyeywords: Domestic Violence, Violence Against Women, Agent-Based Models, Pandemics, Simulation, Metropolitan Regions
Abstract: Violence against women occurs predominantly in the family and domestic context. The COVID-19 pandemic has led Brazil to recommend and at times, impose social distancing, with the partial closure of economic activities, schools, and restrictions on events and public services. Preliminary evidence shows that intense coexistence increases domestic violence, while social distancing measures may have prevented access to public services and networks, information, and help. We propose an agent-based model (ABM), called VIDA, to formalize and illustrate a multitude of factors that influence events which could trigger violence. A central part of the model is the construction of a stress indicator, created as a probability trigger of domestic violence occurring within the family environment. Having a formal model that replicates observed patterns of violence based on internal familial characteristics enables us to experiment with altering dynamics. We first tested the (a) absence or presence of the deterrence system of domestic violence against women and then (b) the existence of measures to increase social distancing. VIDA presents comparative results for metropolitan regions and neighborhoods considered in the experiments. Results suggest that social distancing measures, particularly those encouraging staying at home, may have increased domestic violence against women by about 10%. VIDA suggests further that more populated areas have comparatively fewer cases per hundred thousand women than less populous capitals or rural areas of urban concentrations. This paper contributes to the literature by formalizing, to the best of our knowledge, the first model of domestic violence through agent-based modeling, using empirical detailed socioeconomic, demographic, educational, gender, and race data at the intraurban (census sectors) and household level.

Calibrating Agent-Based Models of Innovation Diffusion with Gradients

Florian Kotthoff and Thomas Hamacher
Journal of Artificial Societies and Social Simulation 25 (3) 4

Kyeywords: Agent-Based Modeling, Multi-Agent Simulation, Innovation Diffusion, Adoption Model, Decision Making, Calibration
Abstract: Consumer behavior and the decision to adopt an innovation are governed by various motives, which models find difficult to represent. A promising way to introduce the required complexity into modeling approaches is to simulate all consumers individually within an agent-based model (ABM). However, ABMs are complex and introduce new challenges. Especially the calibration of empirical ABMs was identified as a key difficulty in many works. In this work, a general ABM for simulating the Diffusion of Innovations is described. The ABM is differentiable and can employ gradient-based calibration methods, enabling the simultaneous calibration of large numbers of free parameters in large-scale models. The ABM and calibration method are tested by fitting a simulation with 25 free parameters to the large data set of privately owned photovoltaic systems in Germany, where the model achieves a coefficient of determination of R2 ≃ 0.7.