Mobilizing for change: simulating political movements in armed conflicts

Theories on the establishment and propagation of political movements through mobilization have emerged and evolved over the last half century. Among the major theoretical frameworks that have been advanced are resource mobilization theory, political process theory, and culture theory. However, despite these developments, relatively few methodological approaches have applied bottom-up computational modeling and simulation in explaining movement development in conflicts. With developments made in computational methods, the integration of social theory with modeling and simulation is a natural progression in creating tools that allow analysts, policy makers, and researchers the means to assess the successes or failures of political movements during armed struggles. This article presents an agent-based model and simulation that applies several frequently used theoretical approaches to political mobilization and explores the extent to which group resources and identity shaped conflicts in Central Asia. Given their historical, cultural, political, economic, and geographical circumstances, the authors seek to determine why different movements experienced contrasting political mobilization outcomes. Results show that receiving outside resources could help a relatively weak group, with limited mobilization, overcome opposition that is initially better mobilized, while shared identity and sufficient risk taking are shown to be potentially strong factors in producing successful mobilization. More broadly, the approach advanced enables analysts and researchers to better anticipate future mobilization events and projected paths of conflict by developing and understanding cause and effect relationships within relevant theoretical frameworks

Simulation and real-time optimal scheduling: a framework for integration

Traditional scheduling and simulation models of the same system differ in several fundamental respects. These include the definition of a schedule, the existence of an objective function which orders schedules and indicates the performance of a given schedule according to specific criteria, and the level of fidelity at which the items are represented and processed through he system. This paper presents a conceptual, object-oriented, architecture for combining a traditional, high-level, scheduling system with a detailed, process- level, discrete-event simulation. A multi-echelon planning framework is established in the context of modeling end-to-end military deployments with the focus on detailed seaport operations

A Block-Free Distributed Ledger for P2P Energy Trading:Case with IOTA?

& #x00A9; 2019, Springer Nature Switzerland AG. Across the world, the organisation and operation of the electricity markets is quickly changing, moving towards decentralised, distributed, renewables-based generation with real-time data exchange-based solutions. In order to support this change, blockchain-based distributed ledgers have been proposed for implementation of peer-to-peer energy trading platform. However, blockchain solutions suffer from scalability problems as well as from delays in transaction confirmation. This paper explores the feasibility of using IOTA’s DAG-based block-free distributed ledger for implementation of energy trading platforms. Our agent-based simulation research demonstrates that an IOTA-like DAG-based solution could overcome the constraints that blockchains face in the energy market. However, to be usable for peer-to-peer energy trading, even DAG-based platforms need to consider specificities of energy trading markets (such as structured trading periods and assured confirmation of transactions for every completed period)

A model based approach for complex dynamic decision-making

Current state-of-the-practice and state-of-the-art of decision-making aids are inadequate for modern organisations that deal with significant uncertainty and business dynamism. This paper highlights the limitations of prevalent decision-making aids and proposes a model-based approach that advances the modelling abstraction and analysis machinery for complex dynamic decision-making. In particular, this paper proposes a meta-model to comprehensively represent organisation, establishes the relevance of model-based simulation technique as analysis means, introduces the advancements over actor technology to address analysis needs, and proposes a method to utilise proposed modelling abstraction, analysis technique, and analysis machinery in an effective and convenient manner. The proposed approach is illustrated using a near real-life case-study from a business process outsourcing organisation

Juxtaposition of system dynamics and agent-based simulation for a case study in immunosenescence

Advances in healthcare and in the quality of life significantly increase human life expectancy. With the aging of populations, new un-faced challenges are brought to science. The human body is naturally selected to be well-functioning until the age of reproduction to keep the species alive. However, as the lifespan extends, unseen problems due to the body deterioration emerge. There are several age-related diseases with no appropriate treatment; therefore, the complex aging phenomena needs further understanding. It is known that immunosenescence is highly correlated to the negative effects of aging. In this work we advocate the use of simulation as a tool to assist the understanding of immune aging phenomena. In particular, we are comparing system dynamics modelling and simulation (SDMS) and agent-based modelling and simulation (ABMS) for the case of age-related depletion of naive T cells in the organism. We address the following research questions: Which simulation approach is more suitable for this problem? Can these approaches be employed interchangeably? Is there any benefit of using one approach compared to the other? Results show that both simulation outcomes closely fit the observed data and existing mathematical model; and the likely contribution of each of the naive T cell repertoire maintenance method can therefore be estimated. The differences observed in the outcomes of both approaches are due to the probabilistic character of ABMS contrasted to SDMS. However, they do not interfere in the overall expected dynamics of the populations. In this case, therefore, they can be employed interchangeably, with SDMS being simpler to implement and taking less computational resources

Describing economic agent-based models – Dahlem ABM documentation guidelines

Wolf S, Bouchaud J-P, Cecconi F, et al. Describing economic agent-based models – Dahlem ABM documentation guidelines. Complexity Economics. 2013;2(1):63-74.At the 100th Dahlem conference “New Approaches in Economics after the Financial Crisis” a working group devised guidelines for the documentation of computational economic agent-based models, based upon – but differing from – the ODD protocol Grimm et al. (2006, 2010). This paper sketches the motivation for coming up with a new set of guidelines tailored to economic multi-agent modelling, and presents these. While analytical economic models can often be precisely and concisely stated by a few equations together with an economic interpretation of their elements, a computational agentbased model, as a conceptual piece of work, may not always be a very tangible entity. For example, it is represented by but usually not identical to the (many) equations constituting the computer code. It is therefore not always easy to describe the model in a way that provides the reader with a thorough understanding of the model. The present guidelines are an attempt at standardizing such descriptions to support understanding and communication, as well as the comparability of economic multi-agent models

The Equifinality of Archaeological Networks: an Agent-Based Exploratory Lab Approach

When we find an archaeological network, how can we explore the necessary versus contingent processes at play in the formation of that archaeological network? Given a set of circumstances or processes, what other possible network shapes could have emerged? This is the problem of equifinality, where many different means could potentially arrive at the same end result: the networks that we observe. This paper outlines how agent-based modelling can be used as a laboratory for exploring different processes of archaeological network formation. We begin by describing our best guess about how the (ancient) world worked, given our target materials (here, the networks of production and patronage surrounding the Roman brick industry in the hinterland of Rome). We then develop an agent-based model of the Roman extractive economy which generates different kinds of networks under various assumptions about how that economy works. The rules of the simulation are built upon the work of Bang (2006; 2008) who describes a model of the Roman economy which he calls the ‘imperial Bazaar’. The agents are allowed to interact, and the investigators compare the kinds of networks this description generates over an entire landscape of economic possibilities. By rigorously exploring this landscape, and comparing the resultant networks with those observed in the archaeological materials, the investigators will be able to employ the principle of equifinality to work out the representativeness of the archaeological network and thus the underlying processes

Production of CXC and CC chemokines by human antigen-presenting cells in response to Lassa virus or closely related immunogenic viruses, and in cynomolgus monkeys with lassa fever.

International audienceThe pathogenesis of Lassa fever (LF), a hemorrhagic fever endemic to West Africa, remains unclear. We previously compared Lassa virus (LASV) with its genetically close, but nonpathogenic homolog Mopeia virus (MOPV) and demonstrated that the strong activation of antigen-presenting cells (APC), including type I IFN production, observed in response to MOPV probably plays a crucial role in controlling infection. We show here that human macrophages (MP) produce large amounts of CC and CXC chemokines in response to MOPV infection, whereas dendritic cells (DC) release only moderate amounts of CXC chemokines. However, in the presence of autologous T cells, DCs produced CC and CXC chemokines. Chemokines were produced in response to type I IFN synthesis, as the levels of both mediators were strongly correlated and the neutralization of type I IFN resulted in an inhibition of chemokine production. By contrast, LASV induced only low levels of CXCL-10 and CXCL-11 production. These differences in chemokine production may profoundly affect the generation of virus-specific T-cell responses and may therefore contribute to the difference of pathogenicity between these two viruses. In addition, a recombinant LASV (rLASV) harboring the NP-D389A/G392A mutations, which abolish the inhibition of type I IFN response by nucleoprotein (NP), induced the massive synthesis of CC and CXC chemokines in both DC and MP, confirming the crucial role of arenavirus NP in immunosuppression and pathogenicity. Finally, we confirmed, using PBMC samples and lymph nodes obtained from LASV-infected cynomolgus monkeys, that LF was associated with high levels of CXC chemokine mRNA synthesis, suggesting that the very early synthesis of these mediators may be correlated with a favourable outcome

IL-2 Immunotherapy to Recently HIV-1 Infected Adults Maintains the Numbers of IL-17 Expressing CD4+ T (TH17) Cells in the Periphery

Little is known about the manipulation of IL-17 producing CD4+ T cells (TH17) on a per-cell basis in humans in vivo. Previous studies on the effects of IL-2 on IL-17 secretion in non-HIV models have shown divergent results. We hypothesized that IL-2 would mediate changes in IL-17 levels among recently HIV-1-infected adults receiving anti-retroviral therapy. We measured cytokine T cell responses to CD3/CD28, HIV-1 Gag, and CMV pp65 stimulation, and changes in multiple CD4+ T cell subsets. Those who received IL-2 showed a robust expansion of naive and total CD4+ T cell counts and T-reg counts. However, after IL-2 treatment, the frequency of TH17 cells declined, while counts of TH17 cells did not change due to an expansion of the CD4+ naïve T cell population (CD27+CD45RA+). Counts of HIV-1 Gag-specific T cells declined modestly, but CMV pp65 and CD3/CD28 stimulated populations did not change. Hence, in contrast with recent studies, our results suggest IL-2 is not a potent in vivo regulator of TH17 cell populations in HIV-1 disease. However, IL-2-mediated T-reg expansions may selectively reduce responses to certain antigen-specific populations, such as HIV-1 Gag