Social Simulation

n this paper, we trace a line through the recent story of agent-based social simulation from the point of view of the LABBS, the laboratory of agent-based so- cial simulation that Cristiano Castelfranchi has contributed to create and helped grow. From this observatory, we deploy a set of arguments defending the need for social simulation as one of the best chances we have to make a much needed step forward in the scientific endeavor of the twenty first century: understanding society. Building on these arguments, we point out several reasons that caused social simulation to fall several measures short of the big challenge, discussing some famous examples from the literature. We then introduce the concept of crowdsourcing, trying to elaborate on how it could reshape this methodology for computational social science.

Agent-based social simulations are typically described in imperative form. While this facilitates implementation as computer programs, it makes implicit the different assumptions made, both about the functional form and the causal ordering involved. As a solution to the problem, a probabilistic graphical model, Action Network (AN), is proposed in this paper for social simulation. Simulation variables are represented by nodes, and causal links by edges. An Action Table is associated with each node, describing incremental probabilistic actions to be performed in response to fuzzy parental states. AN offers a graphical causal model that captures the dynamics of a social process. The details of the formalism are presented, along with illustrative examples. A software implementing the formalism is available in http://actionnetwork.epizy.com.

Social relationships such as friendship and partner choice are ruled by the proximity principle, which states that the more similar two individuals are, the more likely they will become friends. However, proximity, similarity, and friendship are concepts with blurred edges and imprecise grades of membership. This study shows how to simulate these friendship dynamics in an agent-based model that applies fuzzy sets theory to implement agent attributes, rules, and social relationships, explaining the process in detail. Although in principle it may be thought that the use of fuzzy sets theory makes agent-based modelling more elaborated, in practice it saves the modeller from taking some arbitrary decisions on how to use crisp values for representing properties that are inherently fuzzy. The consequences of applying fuzzy sets and operations to define a fuzzy friendship relationship are compared with a simpler implementation, with crisp values. By integrating agent computational models and fuzzy set theory, this paper provides useful insights into scholars and practitioners to tackle the uncertainty inherent to social relationships in a systematic way.

Storicamente il cristianesimo deve molto al giudaismo. Il cristianesimo di San Paolo, tuttavia, ha cambiato il modo di ragionare su concetti come il se, il corpo, e la cognizione umana. Senza volere trattare certi concetti teologici, mi prefiggo di sottolineare come il punto di vista della scienza moderna e piu vicino al giudaismo tradizionale che al cristianesimo, e di spiegare la diffusione dell’“errore” di Paolo nel mondo occidentale, analizzando la semantica dei riferimenti linguistici (e in particolar modo le metafore e le metonimie) dei concetti anima e corpo e del rapporto con la concezione del se. Cresciuto da “uomo franco” cioe, da cittadino romano in un ambiente cosmopolita, Paolo e considerato il testimone piu influente e produttivo del pensiero cristiano nell’Asia Minore e nell’Europa Occidentale. Le sue epistole circolarono durante la sua vita e continuano ad influenzare miliardi di seguaci, i quali spesso interpretano le sue idee in modo contrastante, ma ciononostante ...

Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inherently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective research case studies. Firstly, the complex network modeling level of the proposed framework entails the development of appropriate complex network models for the case where interaction data of cas components is available, with the aim of detecting emergent patterns in the cas under study. The exploratory agent-based modeling level of the proposed framework allows for the development of proof-of-concept models for the cas system, primarily for purposes of exploring feasibility of further research. Descriptive agent-based modeling level of the proposed framework allows for the use of a formal step-by-step approach for developing agent-based models coupled with a quantitative complex network and pseudocode-based specification of the model, which will, in turn, facilitate interdisciplinary cas model comparison and knowledge transfer. Finally, the validated agent-based modeling level of the proposed framework is concerned with the building of in-simulation verification and validation of agent-based models using a proposed Virtual Overlay Multiagent System approach for use in a systematic team-oriented approach to developing models. The proposed framework is evaluated and validated using seven detailed case study examples selected from various scientific domains including ecology, social sciences and a range of complex adaptive communication networks. The successful case studies demonstrate the potential of the framework in appealing to multidisciplinary researchers as a methodological approach to the modeling and simulation of cas by facilitating effective communication and knowledge transfer across scientific disciplines without the requirement of extensive learning curves.

Digital markets depend on recommender systems that facilitate the interaction among suppliers, distributors, and consumers; ultimately increasing sales volume and allegedly increasing user utility. Beyond this operational cornerstone, recommender systems also have a passive role on how these markets organize and behave (e.g. funneling consumers into few suppliers or promoting obscure products and services that can better satisfy consumer needs). The potential effect of recommendations appears to be larger on cultural or entertainment and media industries, where product’s uncertainty for consumers and producers is usually high. As such, cultural diversity and market concentration on content platforms (e.g. YouTube, Spotify) are susceptible to the effect of recommendation systems algorithms. The study of diversity has been a focal topic for individual recommendation optimizations, but little attention has been given to aggregated measures of diversity. Previous work on this area states that collaborative based recommender systems have an impact on sales diversity. I expand on this presenting an agent-based model to test the impacts of recommender systems on cultural markets. The model offers a framework to estimate the effects of state-of-the-art content-based and collaborative filtering algorithms on diversity. Early results confirm previous work. Next steps include the use of machine learning algorithms, social influence, and adaptive behavior of users. Current and future work will provide useful insights for marketing modeling, content platform policy, and the use of recommenders in market design.

This paper focuses on an evaluation of public transportation-based employment transportation (ET) services to transport low-wage workers to jobs in the US. We make an attempt to capture a more comprehensive range of intended and unintended outcomes of ET services than those traditionally considered in the case of public transportation services. Using primary data from 23 locations across the country, we present a framework to evaluate how transportation improvements, in interaction with labor markets, can affect users’ short-run economic welfare, users’ long-run human capital accumulation and non-users’ short-run economic welfare. These services were partially funded by a specialized program – the Job Access and Reverse Commute (JARC) program – which was consolidated into larger transit funding programs by recent legislation. In the sites examined, we found that low wage users benefited from self-reported increased access to jobs, improvements in earnings potential, as well as from savings in transport cost and time. Simulations show the potential of users to accrue long-term worklife benefits. At the same time, users may have accrued changes in leisure time as a result of transitioning from unemployment to employment, and generated a range of societal impacts on three classes of non-users: the general tax-paying public, the general commuting public in the service operating area and other low-wage workers in local labor markets.

Keywords:
Employment transportation
Job Access and Reverse Commute
Low-wage worker
NLSY
Longitudinal
Evaluation
Public transportation
Carless
Spatial mismatch
User, non-user and  societal benefits
Worklife benefits

Mesa is an agent-based modeling framework written in Python. Originally started in 2013, it was created to be the go-to tool in for researchers wishing to build agent-based models with Python. Within this paper we present Mesa's design goals, along with its underlying architecture. This includes its core components: 1) the model (Model, Agent, Schedule, and Space), 2) analysis (Data Collector and Batch Runner) and the visualization (Visualization Server and Visualization Browser Page). We then discuss how agent-based models can be created in Mesa. This is followed by a discussion of applications and extensions by other researchers to demonstrate how Mesa design is decoupled and extensible and thus creating the opportunity for a larger decentralized ecosystem of packages that people can share and reuse for their own needs. Finally, the paper concludes with a summary and discussion of future development areas for Mesa.

In the last decade, the investigation of the social complexity has witnessed the rise of Computational Social Science, a research paradigm that heavily relies upon data and computation to foster our understanding of social phenomena. In this field, a key role is played by the explanatory and predictive power of agent-based social simulations that are showing to take advantage of GIS, higher number of agents and real data. We focus GIS based distibuted ABMs. We observed that the density distribution of agents, over the field, strongly impact on the overall performances. In order to better understand this issue, we analyzes three different scenarios ranging from real positioning, where the citizens are positioned according to a real dataset to a random positioning where the agent are positioned uniformly at random on the field. Results confirm our hypothesis and show that an irregular distribution of the agents over the field increases the communication overhead. We provide also an analytic analysis which, in a 2-dimensional uniform field partitioning, is affected by several parameters (which depend on the model), but is also influenced by the density distribution of agents over the field. According to the presented results, we have that uniform space partitioning strategy does not scale on GIS based ABM characterized by an irregular distribution of agents.

"En la actualidad es común encontrar en varios sitio de Internet personajes animados, tratando de hacer la interacción humano máquina mas amigable, pero han pasado por alto la expresión y la interacción con las acciones del usuario. A fin de mejorar esta interacción, es necesario realizar un estudio sobre las expresiones no verbales, así como de los movimientos corporales en una persona, con el fin de comprender y desarrollar un registro de las gesticulaciones.
El propósito de esta tesis no es solo proporcionar un conocimiento de cómo se reúnen y anima las características de un personaje, sino que propone una metodología para el análisis y creación de personajes virtuales. Los cuales permitieron de manera sencilla animar un personaje en flash CS3.
Este documento ha sido diseñado y revisado cuidadosamente para facilitar la creación de personajes animados que expresen comportamientos sociales."

This article examines the role and function of imagination and parasocial (fiction-based) relations among autistic individuals. In interviews with 17 high functioning, autistic young adults describe how they frequently absorb into daydreams, fantasy literature and multiplayer online roleplaying games. These findings diverge from previous cognitive research which suggests that imagination is limited in autistic individuals; a conclusion which is also challenged by scholars in critical autism research. It is suggested that these opposed scholarly views can be bridged analytically and methodologically by separating between interpersonal and intrapersonal imagination, of which only the former, social aspect is affected across the whole autism spectrum.  The results indicate that parasocial relations are used both for pleasure and to cope with adversities, and that imaginary realms serve as optimal autistic spaces for simulating and practicing social interaction. The article moreover provides a comparative discussion on parasocial and supernatural relations.

Computer simulations of social phenomena are used in academic and
non-academic contexts as tools for decision-aiding. By combining social
scientific knowledge, computational power, and large data sets, those systems may be involved in decisions that affect people who are not even aware of the existence of a simulation. This paper reviews topics from the philosophy of technology and computer ethics literatures in order to identify salient ethical issues related to computer simulations and the steps on the software design cycle on which they can be addressed, offering a checklist that can guide how the ethical concerns of stakeholders are listened to and incorporated into the proposed simulation system.

The idea that dreaming is a simulation of the waking world is currently becoming a far more widely shared and accepted view among dream researchers. Several philosophers, psychologists, and neuroscientists have recently characterized dreaming in terms of virtual reality, immersive spatiotemporal simulation, or realistic and useful world simulation. Thus, the conception of dreaming as a simulated world now unifies definitions of the basic nature of dreaming within dream and consciousness research. This novel concept of dreaming has consequently led to the idea that social interactions in dreams, known to be a universal and abundant feature of human dream content, can best be characterized as a simulation of human social reality, simulating the social skills, bonds, interactions, and networks that we engage in during our waking lives. Yet this tempting idea has never before been formulated into a clear and empirically testable theory of dreaming. Here we show that a testable Social Simulation Theory (SST) of dreaming can be formulated, from which empirical predictions can be derived. Some of the predictions can gain initial support by relying on already existing data in the literature, but many more remain to be tested by further research. We argue that the SST should be tested by directly contrasting its predictions with the major competing theories on the nature and function of dreaming, such as the Continuity Hypothesis (CH) and the Threat Simulation Theory (TST). These three major theories of dreaming make differing predictions as to the quality and the quantity of social simulations in dreams. We will outline the first steps towards a theory-and-hypothesis-driven research program in dream research that treats dreaming as a simulated world in general and as a social simulation in particular. By following this research program it will be possible to find out whether dreaming is a relatively unselective and thus probably non-functional simulation of the waking world (CH), a simulation primarily specialized in the simulation of dangerous and threatening events that present important challenges for our survival and prosperity (TST), or whether it is a simulation primarily specialized in training the social skills and bonds most important for us humans as a social species (SST). Whatever the evidence for or against the specific theories turn out to be, in any case the conception of dreaming as a simulated world has already proved to be a fruitful theoretical approach to understanding the nature of dreaming and consciousness.

Tackling globalization is a great challenge – it is both extremely beneficial and essentially problematic.

This comprehensive, multidisciplinary study confronts this ambivalence through the use of computer simulation. It discusses the findings of social interaction and social simulation through the use of understandable global examples. Readers can use this book as a tool to outline significant aspects of intercultural simulation and highlight the issues that need to be considered in the reader’s analysis.

The author leads the reader via sequential narration from a colloquial description of intercultural situations to final simulation prototypes; each step is accompanied by descriptive comments and program code. Social Interaction, Globalization and Computer-aided Analysis shows the reader how to acquire intercultural data from seemingly inconceivable information sources.

Researchers and software developers engaged in interdisciplinary research projects in the field of Human-Computer Interaction will find this book to be a useful companion in their work.

Launched and developed primarily by Kauffman from the end of sixties, NK simulation modelling candidates for capturing networks dynamics. Grounded in reference to biological networks, it has aroused a grate and durable interest in economics and management sciences too. This methodology is split into a version focused on studying proper Boolean networks dynamics, whose trajectories are substantially
conditioned by Boolean functions, and a (much more frequented) version focused on systems co-evolutionary
paths driven by the search for optimizing its fitness value. Besides the unquestionable value of Kauffman’s work for the theoretical implications on evolutionary biology and the strong interest for economics and management sciences, in this chapter failures and limitations of both NK modelling versions
are discussed. In particular, it is shown that as applications try to be more realistic, this modeling becomes hardly treatable from a computational point of view. On the other hand, it is underlined that, especially the fitness landscape version, NK simulation modelling is very useful to show general aspects
of system’s dynamics, and the impossibility to find general optima (excepted for very special and unrealistic cases). This result sounds a sharp criticism to general economic equilibrium, and it is perfectly consistent with Simon’s contributions.

Computer (Agents)-based simulation is for the social sciences a ‘Trojan horse’: they believe to just have a nice platform for running their previous ideas, for having some experimental confirmation and additional data. They do not realize what they will get: new conceptual tools! especially for modeling the micro and macro processes; new models and theories; new hidden phenomena discovered.
Five issues:
The Simulation revolution & the wrong SocialSciences - SocialSimulation interaction
Why “simulation”: a new scientific method
Kinds & Layers of “Sociality”
Cognitive “mediators”- (“stupid” Agents??)
The “invisible hand” and “alienation”

The goal of this thesis is to suggest some ideas to improve the experience of computational modeling in socio-political areas. These suggestions are presented in the form of a computational modeling framework.
In this framework, firstly, we have suggested that modelers view the socio-political systems as some complex adaptive systems and then use complexity-related theories to describe socio-political behaviours. The agent-based modeling methodology is also suggested as the appropriate methodology to implement these behaviours.
However, the most novel idea of this framework is to introduce the evolutionary epistemology as the appropriate epistemology to study and deal with socio-political problems. In fact, we have used this epistemology from the area of philosophy of science as a support for our exploratory agent-based modeling.
We believe that this framework will help researchers to use computational techniques in a better and more helpful way in understanding and even solving socio-political problems.

Among the most pressing challenges for dream science is the difficulty of establishing theoretical unification between the various theories, ideas, and findings that have been presented in the literature to answer the question of how it is possible to construct a solid scientific theory with predictive and explanatory power in dream science. We suggest that the concept of “world-simulation” serves as the core concept for a theoretically unified paradigm to describe and explain dreaming. From this general concept, more specific theories of the function of dreaming can be derived, such as the Threat Simulation Theory (TST) and the Social Simulation Theory (SST), as we argued in our target article. We agree with Dresler that these two functions may not be the only functions of dreaming, but we still have grounds to believe that they are the strongest contenders. In our reply we first clarify why the functions of sleep should be considered separately from the functions of dreaming. Second, we outline what a good scientific theory of dreaming should be like and what it should be capable of. Furthermore, we evaluate the current state of simulation theories within this context. To conclude, we propose that instead of a general multifunctional theory of sleep and dreaming, where no hypothesis is excluded, the future progress of dream science will benefit more from opposing, competing and mutually exclusive theories about the specific functions of dreaming. This, however, demands that the opposing theories and their predictions must be risky, clearly formulated, and empirically testable.

Abstract. This paper draws attention to the importance of replication as a pedagogical driving force in university courses. We discuss some of the overall concepts relating to replication and make the bridge between teaching computational science and experimentation in social ...

Η παρούσα διατριβή διερευνά τον ρόλο της τοπολογίας επικοινωνίας στο μοντέλο πολλαπλών κανονιστικών ισορροπιών (MER model). Συμπεριλαμβάνει επίσης και μια εισαγωγή στις δραστοστρεφείς προσομοιώσεις καθώς και την παρουσίαση κάποιων από τα σημαντικότερα μοντέλα που αφορούν στη δυναμική εξέλιξη των γνωμών μιας τεχνητής κοινωνίας.

The Expressive Intelligence Studio is developing a new approach to freeform conversational interaction in playable media that combines dialogue management, natural language generation (NLG), and natural language understanding. In this paper, we present our method for dialogue generation, which has been fully implemented in a game we are developing called Talk of the Town. Eschewing a traditional NLG pipeline, we take up a novel approach that combines human language expertise with computer generativity. Specifically, this method utilizes a tool that we have developed for authoring context-free grammars (CFGs) whose productions come packaged with explicit metadata. Instead of terminally expanding top-level symbols—the conventional way of generating from a CFG—we employ an unusual middle-out procedure that targets mid-level symbols and traverses the grammar by both forward chaining and backward chaining, expanding symbols conditionally by testing against the current game state. In this paper, we present our method, discuss a series of associated authoring patterns, and situate our approach against the few earlier projects in this area.

Bad News is a game about death notification that combines deep simulation and live performance. After discovering a dead body, the player is tasked with tracking down a next of kin to inform him or her of the death. To do this, the player must discover the identities of both the deceased and next of kin, as well as the current location of the latter. Game-play is underpinned by a rich simulation of a generic small town inhabited by several hundred non-player characters (NPCs) who build up subjective knowledge of one another as the simulation proceeds. The player interface is serviced by Wizard-of-Oz techniques, and the core gameplay interaction is embodied conversation with live-acted NPCs. Stationed out of sight from the player, a 'wizard' executes his or her commands (as they are spoken aloud) by live-coding modifications to the simulation. When the player encounters an NPC, an actor reveals himself to perform the character live. Crucially, the actor's improvisation is constrained to the underlying simulation—particularly the personality, life history, and knowledge of the character he is portraying— which is expressed to him via a discreet interface.

Our aim is to review the network concept and its relevance on theories of public opinion formation. For this purpose, after discussing social and policy networks, we are reviewing certain network theories of (i) collective action and (ii) voting choices and preferred modes of political participation. Finally, we are presenting a network simulation of public opinion formation that generalizes Axelrod's

The aim of the article is to present the method of social simulation and agent-based modelling in archaeology, a methodological
approach not extensively employed thus far in Czech research. The authors explain the applicability of computer-
constructed social simulation on archaeological data and theoretical questions of current research (e.g. the expansion
of settlement, interaction, economic and subsistence issues, demographic development, etc.). The first part of
the work summarises the related theories of social simulation and agent-based modelling, which are presented as
methods applicable in archaeological research. The process of the creation and use of the model is then explained step
by step, including information on currently discussed methodological questions. The second part of the article presents
several case studies related to the current project focussed on the Late Iron Age in central Europe. These illustrative
issues are chosen to highlight significant aspects of the use of these methodological approaches on specific archaeological
data and domain knowledge, and to foster discussion on the objective advantages and disadvantages of archaeological
interpretations linked to this method.

This paper presents an agent-based social simulation model of the emergence of fashion-like collective behavior designed to explore the role of individual interest and ability to adopt a
fashion trend in the spread of a fashion trend. Results of our simulations show that taking these factors into account leads to more predictive models of fashion-like behavior in populations in a variety of environmental conditions.

El objetivo de este trabajo es presentar la simulacion computacional de un modelo teorico sobre las dinamicas de etnicidad, construido sobre referentes etnoarqueologicos comparables al grado de desarrollo de las sociedades humanas del VI y V milenio en la Peninsula Iberica. Intentamos explicar y justificar el uso de los conceptos de etnicidad y diversidad cultural como categorias dentro del campo de la simulacion computacional, cuya aplicacion dinamica puede proyectarse dentro del campo de la arqueologia de sociedades cazadoras-recolectoras y en su transformacion hacia sociedades neoliticas.

Los modelos basados en agentes (MBA) constituyen una nueva generación de métodos computacionales que permiten modelar la estructura de un sistema complejo y simular su evolución dinámica a lo largo del tiempo. El uso de los mba constituye una tendencia metodológica en expansión en las ciencias sociales contemporáneas; sin embargo, continúan siendo poco conocidos y enseñados en el campo sociológico, de modo que constituyen una alternativa metodológica minoritaria entre los investigadores sociales. El propósito de este trabajo es introducir a los científicos sociales en las ideas centrales de los modelos basados en agentes a partir de su articulación con ciertos problemas teóricos y metodológicos cruciales de las ciencias sociales. La primera sección problematiza la relación entre los modelos basados en agentes y los sistemas complejos en una perspectiva epistemológica crítica. Posteriormente, se analizan los aportes de los mba a la investigación social, y en la tercera sección se evalúa críticamente su aplicación en el marco de una disciplina particular: la ciencia política. Finalmente, se desarrolla un ejemplo práctico de una simulación basada en agentes a partir del trabajo clásico de Thomas Schelling sobre segregación racial.
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Agent-based models (abm) constitute a new generation of computer based methods that allow the modeling of the structure of a complex system and simulation of its dynamic evolution over time. The use of abm constitutes a methodological tendency expanding in contemporary social sciences; however, these models remain quite unknown and not frequently taught in the field of sociology. They therefore represent a minor methodological alternative among social researchers. The purpose of this work is to introduce social scientists to the main ideas of the agent-based models as they are articulated with certain theoretical and methodological problems of the social sciences. The first section puts into question the relationship between agent-based models and complex systems in a critical epistemological perspective. Subsequently, the contributions of abm to social research are analyzed, and in the third section, their application in the framework of a specific discipline, political science, is assessed. Finally, a practical example of a simulation based on agents from the classic work of Thomas Schelling about racial segregation is developed.