This research on the early metal ages of the Wadi el-Hasa focuses on settlement systems and attempts to explain how social, economic and political adjustments helped tribal groups survive under natural (i.e., climatic) and anthropogenic (i.e., land degradation, erosion) stress factors. The shifting of subsistence base from agropastoral to pastoral is reflected in site and population densities, diversity of site types, levels of internal complexity, and levels of social organization via the presence of large settlements, like villages, which acted as economic and administrative centers emerge as risk reduction mechanisms.
The cycles of abandonment and resettlement are evaluated within the concept of social reorganization and such changes are assessed as parts of economic revitalization attempts. The social changes that emerge from such shifts are evaluated from the perspective of the scale-free networks modeled and tested through statistical methods, such as ANOVA, for spatial and temporal patterns, while patterns of land use and the impacts of changing climate and anthropogenic activities are evaluated with GIS.
Following the dimorphic society and heterarchic social organization concepts, the discussion emphasizes that tribal groups adjust population density, range and intensity of activities in marginal landscapes, like the Hasa, in order to prevent environmental degradation. These patterns may change once these marginal landscapes are integrated to more complex social organizations. Although this takes place in the Hasa during the Iron Age, the research results imply that environmental degradation did not take place possibly due to the continuation of extensive subsistence patterns, along with the emergence of the long-distance caravan trade as a major economic incentive.
Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.
To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.
This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.
This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.
This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.
