The emergence of specialization in heterogeneous artificial agent populations

In this dissertation, I present the Weight-Allocated Social Pressure System (WASPS). WASPS is a computational framework that when applied, can allow for the increase in agent specialization within a multi-agent population. Research has shown that specialization can lead to an overall increase in the productivity levels within a population [55]. WASPS aims to provide a mix of features from existing frameworks such as the genetic threshold and social inhibition models. It also subsumes these models, and allows hybrids of them to be created. It provides individual level behaviour as found in the genetic threshold model. As in some variations of the genetic threshold model [49], WASPS also allows for individual level learning. As found in the social inhibition models, WASPS allows for social influence, or population level learning. Unlike some models, WASPS allows agents to self-organize based on available tasks. In addition, it makes allowances for agents to allocate a resource among multiple tasks during a work period, wherein most models allow the selection of only one task. WASPS allows the assumption that agents are heterogeneous in their task performance aptitudes. It thus aims to create skill-based agent specialization within the population. This will allow more skilled agents to allocate more resources to tasks for which they have comparative advantages over their competition. Because WASPS is self-organizing, it can handle the addition and removal of agents from social networks, as well as changes in the connections between agents. WASPS does not limit the definition of many or its parameters, which allows it to deal with changing definitions for those parameters. For example, WASPS can easily adjust to deal with changing definitions of agent skill and influence. In fact, the individual level learning can be implemented in such a way that an agent can self-optimize even when it has no competitors to influence it

The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region

The initial version of the model used in this study, Village 1.0, was implemented by Tim Kohler and a team of developers mostly from Washington State University. The original model addressed environmental constraints only and did not attempt to model social interaction. In a recent paper we employed Cultural Algorithms as a framework in which to add selected social considerations. In this paper we extend our previous model by adding the ability of agents to perform symmetrically initiated or asymmetrically initiated generalized reciprocal exchange. We have developed a state model for agents' knowledge and, given agents' different responses based on this knowledge. Experiments have shown that the network structure of the systems without reciprocity was the simplest but least resilient. As we allowed agents more opportunities to exchange resources we produced more complex network structures, larger populations, and more resilient systems. Furthermore, allowing the agents to buffer their requests by using a finite state model improved the relative resilience of these larger systems. Introducing reciprocity that can be triggered by both requestors and donors produced the largest number of successful donations. This represents the synergy produced by using the information from two complementary situations within the network. Thus, the network has more information with which it can work and tended to be more resilient than otherwise.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44742/1/10588_2004_Article_5270975.pd

Learning and adaptation strategies for evolving artifact capabilities

In this study we address enhancing the ability of social agents embedded in multi-agent based simulations to achieve their goals by using objects in their environment as artifacts. Reformulated as a discrete optimization problem solved with evolutionary computation methods, social agents are empowered to learn and adapt through observations of their own behavior, others in the environment and their community at large. An implemented case study is provided incorporating the model into the multi-agent simulation of the Village EcoDynamics Project developed to study the early Pueblo Indian settlers from A.D. 600 to 1300. Eliminating the existing presumption that agents automatically know the productivity of the landscape as part of their settling and farming practices, agents use the landscape as an artifact, learning to predict its productivity from a few attributes such as the area's slope and aspect. Given the dynamic nature of the landscape and its inhabitants, agents also evolve various combinations of learning strategies adapting to meet their needs. The result is the demonstration of a mechanism for incorporating artifact use learning and evolution in social simulations, leading to the emergence of favorable learning strategies

EUSN 2021 Book of Abstracts, Fifth European Conference on Social Networks

Book of abstract of the fifth European conference on Social Networks EUSN 202

Social capital and rural development: literature review and current state of the art

Social capital has been recently held up as a conceptual framework to build a bridge between the diverse disciplines involved in rural development. However, despite its potential and the impressively rapid take-up of the concept by the community of development professionals, it remains an elusive construct. No definition is yet generally accepted and many definitions are in use. Recently, social capital in the form of social networks has gained much attention in rural development theory and empirical research. But social networks or structural components of social capital are a largely missing dimension in income and poverty analysis. Moreover, most research on social capital assumes that it is a uniform entity. Therefore, the effects of different forms of social capital on household outcome are rarely investigated. The objective of this discussion paper is to make the concept of social capital more tangible for empirical research in the area of rural development and to bring more structure into the conceptual framework of social capital. On the basis of an extensive literature review, this work proposes a lean and clear definition of social capital: Social capital is conceived as networks plus resources, (e.g. credit, information). Moreover, social capital is assumed to be not a homogeneous entity. Hence, it is necessary to distinguish different forms of social capital. For analytical purposes, the separation into so-called bonding and bridging capital seems to be most appealing. These two forms of social capital can be operationalized as function of an agent's so-called weak ties (e.g. acquaintances) and so-called strong ties (e.g. close relatives). -- G E R M A N V E R S I O N: Sozialkapital hat innerhalb der letzten zwei Jahrzehnte als interdisziplinäres Konzept eine enorme Bedeutung sowohl in der Wissenschaft als auch in der praktischen ländlichen Entwicklung erlangt. Trotz eines ‚Booms’ an wissenschaftlichen und nicht wissenschaftlichen Arbeiten bleibt das Konzept wenig greifbar. Bisher konnte sich die wissenschaftliche Gemeinde auf keine allgemeingültige Definition einigen. Sehr unterschiedliche und zum Teil sehr umfassende Definitionen sind in Gebrauch. Neuere Arbeiten tendieren allerdings dazu, Sozialkapital enger zu definieren und Netzwerke in den Vordergrund zu stellen. Nichtsdestotrotz werden strukturelle Komponenten von Sozialkapital oder Netzwerken nur selten in Einkommens- und Armutsanalysen einbezogen. Es wird auch noch oft unterstellt, dass Sozialkapital eine homogene Ressource ist. Deshalb werden dessen unterschiedlichen Ausprägungen noch seltener untersucht. Das Hauptziel dieses Diskussionspapiers ist es, einen geeigneten Ansatz für die empirische Forschung im Bereich ländlicher Entwicklung, basierend auf dem Netzwerkansatz, herauszuarbeiten. Basierend auf einer intensiven Literaturrecherche empfiehlt das Papier eine klare und einfache Definition von Sozialkapital. Sozialkapital wird als Netzwerk plus Ressourcen definiert. Unterschiedliche Formen von Sozialkapital (‚Bonding’ und ‚Bridging’) werden über die Stärke der Beziehung der Netzwerkteilnehmer bestimmt.Social capital,individual social capital,measuring social capital,ego-network,social networks

Agent-based modeling for migration and modern slavery research: a systematic review

AbstractThis systematic review aims to synthesize how agent-based modeling (ABM) has been used in migration and modern slavery research and provide the basis to model development for social science researchers exploring the use of ABM. We searched five bibliographic databases using two terminology categories: (1) migration or modern slavery terminology; (2) complex system methods terminology. Two reviewers conducted independent article screening. Peer-reviewed articles presenting original migration or modern slavery ABMs were included. Data extraction included model development steps and model characteristics. The dataset was synthesized and compared across studies. We identified 28 articles for inclusion. Many of the ABMs tested theories and about half were based on empirical data. Model development varied considerably and reported methods were extremely opaque. Only five studies used a structured development framework. The most common model involved agents deciding whether and where to migrate and attempting migration. Climate change was a common exogenous scenario modeled. Most of the ABMs did not undergo any sensitivity analysis or validation.ABM has a greater capacity to account for heterogeneous and dynamic decision-making than more frequently applied methods in research on migration and modern slavery. However, there is still a paucity of studies adopting ABM methods. These reviewed ABMs highlight gaps in the reporting and implementing of model development. ABM is a promising technique to address many urgent and complex questions in research on migration and modern slavery to better support decision-makers, but addressing current methodological gaps is a critical first step.</jats:p

Unraveling the unsustainability spiral in sub-saharan Africa: an agent based modelling approach

Sub-Saharan Africa is trapped in a complex unsustainability spiral with demographic, biophysical, technical and socio-political dimensions. Unravelling the spiral is vital to perceive which policy actions are needed to reverse it and initiate sustainable pro-poor growth. The article presents an evolutionary, multi-agent modelling framework that marries a socio-ecological approach to a world system perspective and takes agriculture as the engine for sustainable development in sub-Saharan Africa. A number of possibilities for empirical validation are proposed

Scale Matters: The Quality of Quantity in Human Culture and Sociality

Scale matters. When conducting research and writing, scholars upscale and downscale. So do the subjects of their work - we scale, they scale. Although scaling is an integrant part of research, we rarely reflect on scaling as a practice and what happens when we engage with it in scholarly work. The contributors aim to change this: they explore the pitfalls and potentials of scaling in an interdisciplinary dialogue. The volume brings together scholars from diverse fields, working on different geographical areas and time periods, to engage with scale-conscious questions regarding human sociality, culture, and evolution. With contributions by Nurit Bird-David, Robert L. Kelly, Charlotte Damm, Andreas Maier, Brian Codding, Elspeth Ready, Bram Tucker, Graeme Warren and others