Simulation Approaches for System of Systems: Event-Based Versus Agent Based Modeling

This paper from the 2015 Conference on Systems Engineering Research conference proceedings reviews different modeling techniques and uses two converse techniques, i.e. agent-based and event-based modeling, to run a simulation of hypothetical systems collaborating into a system of systems

Agent-Based Computational Models - A Formal Heuristic for Institutionalist Pattern Modelling?

Institutionalist economists have always been criticizing the neoclassical way of studying the economy, especially because of its obsession to a very strict and flawed formalism. This formalism receives critique also from advocates of agent-based computational economic (ACE) models. The criticism seems to be similar to that of institutional economists. Although some authors consider ACE models to belong to a completely new way of thinking about economics, many concepts of ACE have been anticipated by institutionalists: Although using a different vocabulary, ACE proponents speak about cumulative causation, realistic agents, explanatory models, dynamic relations among individuals and the necessity to see the economy as an systemic whole rather than from an atomistic perspective. Consequently, the emergence of the ACE framework may not be left unconsidered by institutionalist economists. This paper investigates the consistency of ACE models with the institutionalist research program as defined by Myrdal, Wilber and Harrison and other original institutionalists and discusses whether ACE models can be a useful heuristic for institutionalist "pattern modelling". I study the ability of ACE models to provide a holistic, systemic and evolutionary picture of the economy, the conception of agents in ACE models, and ask whether they can help to understand the social stratification of a society with its power relations. I also compare ACE models with earlier attempts to formalize institutionalist analysis, e.g. by Bush and Elsner (Theory of Institutional Change), Hayden (Social-­Fabric-Matrix) or Radzicki (System Dynamics)

Cost-Effectiveness Analysis Using Agent-Based Modelling: A General Framework with Case Studies

In recent years, agent-based modelling (ABM) has been increasingly used to elucidate complex adaptive systems. An ABM is a structural computational system that consists of a collection of abstract objects (agents) embedded in a virtual environment that interact based on a set of prescribed rules. While traditional approaches such as differential equation-based compartmental models span a vast literature, they often impose restrictive assumptions such as homogeneity and determinism that limit their application to real settings. ABM overcomes these limitations through a bottom-up approach in which macro dynamics emerge from micro level phenomena. During the past decade, there has been a surge of interest in the use of ABM in human health and disease dynamics. While this is rapidly growing, its application to other relevant areas such as health economics is still in infancy, and frameworks that could systematically apply ABM are still lacking. In this thesis, we develop a general framework for cost-effectiveness analysis in which ABM is designed to project the system dynamics. We argue that ABM improves the empirical reliability of policy-oriented simulation models and that it presents an ideal tool to address the complexity of disease processes, project the impact of interventions and inform their optimal implementation. We use this framework in an epidemiological context to quantify the economic impact of vaccination strategies for prevention of infectious diseases. We present two case studies for a human-to-human infection transmission (i.e., Haemophilus influenzae) and a vector-borne disease (i.e., Zika). In each case, we detail the construction of ABM and its utilization to conduct Bayesian cost-effectiveness analysis of potential vaccine candidates. In addition to uncovering important characteristics of these diseases in epidemic dynamics, we present their first cost-effectiveness analysis and implications for vaccination strategies in different populations settings