Augmenting Bottom-Up Metamodels with Predicates

Metamodeling refers to modeling a model. There are two metamodeling approaches for ABMs: (1) top-down and (2) bottom-up. The top down approach enables users to decompose high-level mental models into behaviors and interactions of agents. In contrast, the bottom-up approach constructs a relatively small, simple model that approximates the structure and outcomes of a dataset gathered fromthe runs of an ABM. The bottom-up metamodel makes behavior of the ABM comprehensible and exploratory analyses feasible. Formost users the construction of a bottom-up metamodel entails: (1) creating an experimental design, (2) running the simulation for all cases specified by the design, (3) collecting the inputs and output in a dataset and (4) applying first-order regression analysis to find a model that effectively estimates the output. Unfortunately, the sums of input variables employed by first-order regression analysis give the impression that one can compensate for one component of the system by improving some other component even if such substitution is inadequate or invalid. As a result the metamodel can be misleading. We address these deficiencies with an approach that: (1) automatically generates Boolean conditions that highlight when substitutions and tradeoffs among variables are valid and (2) augments the bottom-up metamodel with the conditions to improve validity and accuracy. We evaluate our approach using several established agent-based simulations

A Generative Model of the Mutual Escalation of Anxiety Between Religious Groups

We propose a generative agent-based model of the emergence and escalation of xenophobic anxiety in which individuals from two different religious groups encounter various hazards within an artificial society. The architecture of the model is informed by several empirically validated theories about the role of religion in intergroup conflict. Our results identify some of the conditions and mechanisms that engender the intensification of anxiety within and between religious groups. We define mutually escalating xenophobic anxiety as the increase of the average level of anxiety of the agents in both groups overtime. Trace validation techniques show that the most common conditions under which longer periods of mutually escalating xenophobic anxiety occur are those in which the difference in the size of the groups is not too large and the agents experience social and contagion hazards at a level of intensity that meets or exceeds their thresholds for those hazards. Under these conditions agents will encounter out-group members more regularly, and perceive them as threats, generating mutually escalating xenophobic anxiety. The model\u27s capacity to grow the macro-level emergence of this phenomenon from micro-level agent behaviors and interactions provides the foundation for future work in this domain

The interlocutory tool box: techniques for curtailing coincidental correctness

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonEliminating faults in software systems is important, because they can have catastrophic consequences. This can be achieved by testing and debugging. Testing involves executing the system with a test case to obtain an output. The output is evaluated against the tester’s expectations; deviation from these expectations indicates that a fault has been detected. Debugging involves using information about the fault, that was gleaned during testing, to isolate the fault in the system. Coincidental correctness is a widespread phenomenon in which a fault corrupts a program state, and despite this, the system produces an output that satisfies the tester’s expectations. Coincidental correctness can compromise the effectiveness of testing and debugging techniques. This thesis investigated methods for alleviating coincidental correctness in testing and debugging. The investigation culminated in four techniques. The first technique is called Interlocutory Testing. Interlocutory Testing is a framework for the development of test oracles that are referred to as Interlocutory Relations. Interlocutory Relations are the first type of oracle that has been specifically designed to operate effectively in the presence of coincidental correctness. Metamorphic Testing was pioneered for testing non-testable systems. However, the effectiveness of this technique can be compromised by coincidental correctness. The second technique, Interlocutory Metamorphic Testing, is a version of Metamorphic Testing that has been integrated with Interlocutory Testing, to alleviate the impact of coincidental correctness on Metamorphic Testing. Interlocutory Mutation Testing is the third technique. This technique uses similar principles to Interlocutory Testing to alleviate the Equivalent Mutant Problem in the presence of coincidental correctness and non-determinism. Finally, the fourth technique is Interlocutory Spectrum-based Fault Localisation. This technique uses Interlocutory Relations to ameliorate the effects of coincidental correctness on fault localisation. Each technique was empirically evaluated. The results were promising, and indicated that these techniques were capable of mitigating the impact of coincidental correctness