M. Moglia, C. Nygaard, Stephen Glackin, S. Cook, S. Tapsuwan
: Understanding the processes of residential solar PV uptake is critical to developing planning and policy energy transition pathways. This paper outlines a novel hybrid Agent-Based-Modelling/statistical adoption prediction framework that addresses several drawbacks in current modelling approaches. Specifically, we extend the capabilities of similar previous models and incorporate empirical data, behavioural theory, social networks and explicitly considers the spatial context. We provide empirical data affecting households’ propensity to adopt, including perceptions of solar PV systems, the role of tenure and urban location. We demonstrate the approach in the context of Melbourne metropolitan region, Australia; and draw on housing approval data to demonstrate the role of housing construction in accelerating adoption. Finally, we explore the approach’s validity against real-world data with promising results that also indicate key areas for further research and improvement.
{"title":"Hybrid Approach for Modelling the Uptake of Residential Solar PV Systems, with Case Study Application in Melbourne, Australia","authors":"M. Moglia, C. Nygaard, Stephen Glackin, S. Cook, S. Tapsuwan","doi":"10.18564/jasss.4921","DOIUrl":"https://doi.org/10.18564/jasss.4921","url":null,"abstract":": Understanding the processes of residential solar PV uptake is critical to developing planning and policy energy transition pathways. This paper outlines a novel hybrid Agent-Based-Modelling/statistical adoption prediction framework that addresses several drawbacks in current modelling approaches. Specifically, we extend the capabilities of similar previous models and incorporate empirical data, behavioural theory, social networks and explicitly considers the spatial context. We provide empirical data affecting households’ propensity to adopt, including perceptions of solar PV systems, the role of tenure and urban location. We demonstrate the approach in the context of Melbourne metropolitan region, Australia; and draw on housing approval data to demonstrate the role of housing construction in accelerating adoption. Finally, we explore the approach’s validity against real-world data with promising results that also indicate key areas for further research and improvement.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"331 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77142259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: The academic study and the applied use of agent-based modelling of social processes has matured considerably over the last thirty years. The time is now right to engage seriously with the ethics and responsible practice of agent-based social simulation. In this paper, we first outline the many reasons why it is appropriate to explore an ethics of agent-based modelling and how ethical issues arise in its practice and organisation. We go on to discuss different approaches to standardisation as a way of supporting responsible practice. Some of the main conclusions are organised as provisions in a draft code of ethics. We intend for this draft to be further developed by the community before being adopted by individuals and groups within the field informally or formally.
{"title":"The Ethics of Agent-Based Social Simulation","authors":"D. Anzola, Peter Barbrook-Johnson, N. Gilbert","doi":"10.18564/jasss.4907","DOIUrl":"https://doi.org/10.18564/jasss.4907","url":null,"abstract":": The academic study and the applied use of agent-based modelling of social processes has matured considerably over the last thirty years. The time is now right to engage seriously with the ethics and responsible practice of agent-based social simulation. In this paper, we first outline the many reasons why it is appropriate to explore an ethics of agent-based modelling and how ethical issues arise in its practice and organisation. We go on to discuss different approaches to standardisation as a way of supporting responsible practice. Some of the main conclusions are organised as provisions in a draft code of ethics. We intend for this draft to be further developed by the community before being adopted by individuals and groups within the field informally or formally.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77238590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Williams, Daniel G. Brown, S. Guikema, T. Logan, N. Magliocca, Birgit Müller, C. Steger
: Advancing equity is a complex challenge for society, science, and policy. Agent-based models are increasingly used as scientific tools to advance understanding of systems, inform decision-making, and share knowledge. Yet, equity has not received due attention within the agent-based modeling (ABM) literature. In this paper, wedevelopaconceptualframeworkandprovideguidanceforintegratingequityconsiderationsintoABM researchandmodelingpractice. TheframeworkconceptualizesABMasinterfacingwithequityoutcomesattwo levels(thescience-societyinterfaceandwithinthemodelitself)andthemodelerasa filter and lens thatprojects knowledge between the target system and the model. Within the framework, we outline three complementary, equity-advancing action pathways: (1) engage stakeholders, (2) acknowledge positionality and bias, and (3) assessequitywithagent-basedmodels. ForPathway1,wesummarizeexistingguidancewithintheparticipatory modeling literature. For Pathway 2, we introduce the positionality and bias document as a tool to promote modeler and stakeholder reflexivity throughout the modeling process. For Pathway 3, we synthesize a typology of approaches for modeling equity and offer a set of preliminary suggestions for best practice. By engaging with these action pathways, modelers both reduce the risks of inadvertently perpetuating inequity and harness the opportunities for ABM to play a larger role in creating a more equitable future.
{"title":"Integrating Equity Considerations into Agent-Based Modeling: A Conceptual Framework and Practical Guidance","authors":"T. Williams, Daniel G. Brown, S. Guikema, T. Logan, N. Magliocca, Birgit Müller, C. Steger","doi":"10.18564/jasss.4816","DOIUrl":"https://doi.org/10.18564/jasss.4816","url":null,"abstract":": Advancing equity is a complex challenge for society, science, and policy. Agent-based models are increasingly used as scientific tools to advance understanding of systems, inform decision-making, and share knowledge. Yet, equity has not received due attention within the agent-based modeling (ABM) literature. In this paper, wedevelopaconceptualframeworkandprovideguidanceforintegratingequityconsiderationsintoABM researchandmodelingpractice. TheframeworkconceptualizesABMasinterfacingwithequityoutcomesattwo levels(thescience-societyinterfaceandwithinthemodelitself)andthemodelerasa filter and lens thatprojects knowledge between the target system and the model. Within the framework, we outline three complementary, equity-advancing action pathways: (1) engage stakeholders, (2) acknowledge positionality and bias, and (3) assessequitywithagent-basedmodels. ForPathway1,wesummarizeexistingguidancewithintheparticipatory modeling literature. For Pathway 2, we introduce the positionality and bias document as a tool to promote modeler and stakeholder reflexivity throughout the modeling process. For Pathway 3, we synthesize a typology of approaches for modeling equity and offer a set of preliminary suggestions for best practice. By engaging with these action pathways, modelers both reduce the risks of inadvertently perpetuating inequity and harness the opportunities for ABM to play a larger role in creating a more equitable future.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77260423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Changes in agricultural systems are a multi-causal process involving climate change, globalization and technological change. These complex interactions regulate the landscape transformation process by imposing landuseandcover change (LUCC)dynamics. Inorder tobetterunderstandand forecast theLUCCprocess we developed a spatially explicit agent-based model in the form of a Cellular Automata: the AgroDEVS model. The model was designed to project viable LUCC dynamics along with their associated economic and environmental changes. AgroDEVS is structured with behavioral rules and functions representing a) crop yields, b) weather conditions, c) economic profits, d) farmer preferences, e) adoption of technology levels and f) natural resource consumption based on embodied energy accounting. Using data from a typical location of the Pampa region (Argentina) for the period 1988-2015, simulation exercises showed that economic goals were achieved, on average, each 6 out of 10 years, but environmental thresholds were only achieved in 1.9 out of 10 years. In a set of 50-years simulations, LUCC patterns converge quickly towards the most profitable crop sequences, with no noticeable trade-o between economic and environmental conditions.
{"title":"An Integrated Ecological-Social Simulation Model of Farmer Decisions and Cropping System Performance in the Rolling Pampas (Argentina)","authors":"S. Pessah, D. Ferraro, D. Blanco, R. Castro","doi":"10.18564/jasss.4772","DOIUrl":"https://doi.org/10.18564/jasss.4772","url":null,"abstract":"Changes in agricultural systems are a multi-causal process involving climate change, globalization and technological change. These complex interactions regulate the landscape transformation process by imposing landuseandcover change (LUCC)dynamics. Inorder tobetterunderstandand forecast theLUCCprocess we developed a spatially explicit agent-based model in the form of a Cellular Automata: the AgroDEVS model. The model was designed to project viable LUCC dynamics along with their associated economic and environmental changes. AgroDEVS is structured with behavioral rules and functions representing a) crop yields, b) weather conditions, c) economic profits, d) farmer preferences, e) adoption of technology levels and f) natural resource consumption based on embodied energy accounting. Using data from a typical location of the Pampa region (Argentina) for the period 1988-2015, simulation exercises showed that economic goals were achieved, on average, each 6 out of 10 years, but environmental thresholds were only achieved in 1.9 out of 10 years. In a set of 50-years simulations, LUCC patterns converge quickly towards the most profitable crop sequences, with no noticeable trade-o between economic and environmental conditions.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74246318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Attracting and retaining loyal customers is a key driver of insurance profit. An important factor is the customers’opinionofaninsurer’sservicequality. Ifacustomerhasabadexperiencewithaninsurer,theywillbe less likely to buy from them again. Word-of-mouth networks allow information to spread between customers. In this paper we build an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network. We find that the existence of the network acts as a persistent memory, causing a systemic bias whereby an insurer’s early reputation achieved by random chance tends to persist and leads to unequal market shares. This occurs even when the transmission of information is very low. This suggests that newer insurers might benefit more from a higher service quality as they build their reputation. Insurers with a higher service quality earn more profit, even when the customer preference for better service quality is small. The UK regulator is intending to ban the practice of charging new customers less than renewing customers. When the model is run with this scenario, the retention rates increase substantially and there is less movement away from insurers with a good initial reputation. This increases the skewness in market concentrations, but there is a greater incentive for good service quality.
{"title":"An Agent-Based Model of Motor Insurance Customer Behaviour in the UK with Word of Mouth","authors":"Rei England, Iqbal Owadally, D. Wright","doi":"10.18564/jasss.4768","DOIUrl":"https://doi.org/10.18564/jasss.4768","url":null,"abstract":": Attracting and retaining loyal customers is a key driver of insurance profit. An important factor is the customers’opinionofaninsurer’sservicequality. Ifacustomerhasabadexperiencewithaninsurer,theywillbe less likely to buy from them again. Word-of-mouth networks allow information to spread between customers. In this paper we build an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network. We find that the existence of the network acts as a persistent memory, causing a systemic bias whereby an insurer’s early reputation achieved by random chance tends to persist and leads to unequal market shares. This occurs even when the transmission of information is very low. This suggests that newer insurers might benefit more from a higher service quality as they build their reputation. Insurers with a higher service quality earn more profit, even when the customer preference for better service quality is small. The UK regulator is intending to ban the practice of charging new customers less than renewing customers. When the model is run with this scenario, the retention rates increase substantially and there is less movement away from insurers with a good initial reputation. This increases the skewness in market concentrations, but there is a greater incentive for good service quality.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82607914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. McCulloch, Jiaqi Ge, Jonathan A. Ward, A. Heppenstall, J. Gareth Polhill, N. Malleson
: Agent-based models (ABMs) can be found across a number of diverse application areas ranging from simulating consumer behaviour to infectious disease modelling. Part of their popularity is due to their ability to simulateindividualbehavioursanddecisionsoverspaceandtime. However, whilstthereareplentifulexamples within the academic literature, these models are only beginning to make an impact within policy areas. Whilst frameworks such as NetLogo make the creation of ABMs relatively easy, a number of key methodological issues, including the quantification of uncertainty, remain. In this paper we draw on state-of-the-art approaches from the fields of uncertainty quantification and model optimisation to describe a novel framework for the calibration of ABMs using History Matching and Approximate Bayesian Computation. The utility of the framework is demonstrated on three example models of increasing complexity: (i) Sugarscape to illustrate the approach on a toy example; (ii) a model of the movement of birds to explore the efficacy of our framework and compare it to alternative calibration approaches and; (iii) the RISC model of farmer decision making to demonstrate its value in a real application. The results highlight the efficiency and accuracy with which this approach can be used to calibrate ABMs. This method can readily be applied to local or national-scale ABMs, such as those linked to the creation or tailoring of key policy decisions.
{"title":"Calibrating Agent-Based Models Using Uncertainty Quantification Methods","authors":"J. McCulloch, Jiaqi Ge, Jonathan A. Ward, A. Heppenstall, J. Gareth Polhill, N. Malleson","doi":"10.18564/jasss.4791","DOIUrl":"https://doi.org/10.18564/jasss.4791","url":null,"abstract":": Agent-based models (ABMs) can be found across a number of diverse application areas ranging from simulating consumer behaviour to infectious disease modelling. Part of their popularity is due to their ability to simulateindividualbehavioursanddecisionsoverspaceandtime. However, whilstthereareplentifulexamples within the academic literature, these models are only beginning to make an impact within policy areas. Whilst frameworks such as NetLogo make the creation of ABMs relatively easy, a number of key methodological issues, including the quantification of uncertainty, remain. In this paper we draw on state-of-the-art approaches from the fields of uncertainty quantification and model optimisation to describe a novel framework for the calibration of ABMs using History Matching and Approximate Bayesian Computation. The utility of the framework is demonstrated on three example models of increasing complexity: (i) Sugarscape to illustrate the approach on a toy example; (ii) a model of the movement of birds to explore the efficacy of our framework and compare it to alternative calibration approaches and; (iii) the RISC model of farmer decision making to demonstrate its value in a real application. The results highlight the efficiency and accuracy with which this approach can be used to calibrate ABMs. This method can readily be applied to local or national-scale ABMs, such as those linked to the creation or tailoring of key policy decisions.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84047337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Among social anthropologists, there is virtual consensus that the food-sharing practices of small-scale non-agricultural groups cannot be understood in isolation from the broader repertoire of leveling strategies that prevent would-be dominants from exercising power and influence over likely subordinates. In spite of that widespread view, quantitatively rigorous empirical studies of food sharing and cooperation in small-scale human groups have typically ignored the internal connection between leveling of income and political power, drawing inspiration instead from evolutionary models that are neutral about social role asymmetries. In this paper, I introduce a spatially explicit agent-based model of hunter-gatherer food sharing in which individuals are driven by the goal of maximizing their own income while minimizing income asymmetries among others.
{"title":"Egalitarian Sharing Explains Food Distributions in a Small-Scale Society","authors":"M. Pinheiro","doi":"10.18564/jasss.4835","DOIUrl":"https://doi.org/10.18564/jasss.4835","url":null,"abstract":": Among social anthropologists, there is virtual consensus that the food-sharing practices of small-scale non-agricultural groups cannot be understood in isolation from the broader repertoire of leveling strategies that prevent would-be dominants from exercising power and influence over likely subordinates. In spite of that widespread view, quantitatively rigorous empirical studies of food sharing and cooperation in small-scale human groups have typically ignored the internal connection between leveling of income and political power, drawing inspiration instead from evolutionary models that are neutral about social role asymmetries. In this paper, I introduce a spatially explicit agent-based model of hunter-gatherer food sharing in which individuals are driven by the goal of maximizing their own income while minimizing income asymmetries among others.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74920208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: As the heating of private households represents 16.5% of all EU final energy consumption, household energy retrofitting is a central part of the solution for the ongoing climate crisis. However, ABM models have not sufficiently been explored as a tool for designing policies for reducing household heating energy consumption through energy retrofitting. This paper presents the Household Energy Retrofit Behavior (HERB) model, which simulated energy retrofitting in a neighbourhood. The HERB model feeds a decision-making process based on existing behavioural household retrofit research with survey data and assesses the impact of different policies on cumulative energy need over 100 years. The model finds that the current Norwegian main retrofit subsidies have a positive effect on energy use. Furthermore, although motivating households to retrofit to a specific standard has no positive impact, motivating households close to retrofitting has a positive effect. Finally, lowering the threshold for receiving subsidies has a positive impact.
{"title":"Effect of Policy Implementation on Energy Retrofit Behavior and Energy Consumption in a Simulated Neighborhood","authors":"L. E. Egner, C. Klöckner","doi":"10.18564/jasss.4936","DOIUrl":"https://doi.org/10.18564/jasss.4936","url":null,"abstract":": As the heating of private households represents 16.5% of all EU final energy consumption, household energy retrofitting is a central part of the solution for the ongoing climate crisis. However, ABM models have not sufficiently been explored as a tool for designing policies for reducing household heating energy consumption through energy retrofitting. This paper presents the Household Energy Retrofit Behavior (HERB) model, which simulated energy retrofitting in a neighbourhood. The HERB model feeds a decision-making process based on existing behavioural household retrofit research with survey data and assesses the impact of different policies on cumulative energy need over 100 years. The model finds that the current Norwegian main retrofit subsidies have a positive effect on energy use. Furthermore, although motivating households to retrofit to a specific standard has no positive impact, motivating households close to retrofitting has a positive effect. Finally, lowering the threshold for receiving subsidies has a positive impact.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83435622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Opinion dynamics models have huge potential for understanding and addressing social problems where solutions require the coordination of opinions, like anthropogenic climate change. Unfortunately, to date, most of such models have little or no empirical validation. In the present work we develop an opinion dynamics model derived from a real life experiment. In our experimental study, participants reported their opinions before and after social interaction using response options “agree” or “disagree,” and opinion strength 1 to 10. The social interaction entailed showing the participant their interaction partner’s agreement value on the same topic, but not their certainty. From the analysis of the data, we observed a very weak, but statistically significant influence between participants. We also noticed three important effects. (1) Asking people their opinion is sufficient to produce opinion shift and thus influence opinion dynamics, at least on novel topics. (2) About 4% of the time people flipped their opinion, while preserving their certainty level. (3) People with extreme opinions exhibited much less change than people having neutral opinions. We also built an opinion dynamics model based on the three mentioned phenomena. This model was able to produce realistic results (i.e. similar to real-world data) such as polarization from unpolarized states and strong diversity.
{"title":"Deriving an Opinion Dynamics Model from Experimental Data","authors":"D. Carpentras, P. Maher, C. O'Reilly, M. Quayle","doi":"10.18564/jasss.4947","DOIUrl":"https://doi.org/10.18564/jasss.4947","url":null,"abstract":": Opinion dynamics models have huge potential for understanding and addressing social problems where solutions require the coordination of opinions, like anthropogenic climate change. Unfortunately, to date, most of such models have little or no empirical validation. In the present work we develop an opinion dynamics model derived from a real life experiment. In our experimental study, participants reported their opinions before and after social interaction using response options “agree” or “disagree,” and opinion strength 1 to 10. The social interaction entailed showing the participant their interaction partner’s agreement value on the same topic, but not their certainty. From the analysis of the data, we observed a very weak, but statistically significant influence between participants. We also noticed three important effects. (1) Asking people their opinion is sufficient to produce opinion shift and thus influence opinion dynamics, at least on novel topics. (2) About 4% of the time people flipped their opinion, while preserving their certainty level. (3) People with extreme opinions exhibited much less change than people having neutral opinions. We also built an opinion dynamics model based on the three mentioned phenomena. This model was able to produce realistic results (i.e. similar to real-world data) such as polarization from unpolarized states and strong diversity.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85422381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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