1/29/2024 0 Comments Netlogo breedThe 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.Special: Variables - Keywords - Constants 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. 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. 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. 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. 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. 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. 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. 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. Además, discutimos la epistemología de utilizar modelos computacionales y de simulación, clasificamos los tipos de modelos, y proveemos un resumen de los conceptos principales de los modelos multiagente. En este artículo y el tutorial que lo acompaña, proveemos una introducción a estos métodos, libres de jerga técnica, su potencial y sus límites, y también las diversas aplicaciones en arqueología. Aun así, al ser un método de informática no es aún bien establecido entre la mayoría de arqueólogos. Modelos basados en sistemas multiagente proveen un marco práctico para explorar modelos cuantitativos de sociedades en el pasado. Modelos cuantitativos robustos de sociedades humanas en el pasado tienen el potencial de informar los temas de debate actual, parti-cularmente modelos informados por estudios de arqueología. We discuss the epistemological rationale of using computational modeling and simulation, classify types of models, and give an overview of the main concepts behind agent-based modeling. In this paper and the associated tutorial, we provide a jargon-free introduction to the technique, its potential and limits as well as its diverse applications in archaeology and beyond. However, being derived from computer science, the method remains largely specialized in archaeology. Agent-based models, which emphasize how actions by individuals combine to produce global patterns, provide a convenient framework for developing quantitative models of historical social processes. Formal models of past human societies informed by archaeological research have a high potential for shaping some of the most topical current debates.
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