Peter Fratrič
Mining behavior from a legal simulation environment: where we are and what lies ahead
This talk presents a methodological framework for the use of simulation-based methods to investigate questions of non-compliance in a legal context. Its aim is to generate observed or previously unobserved instances of non-compliance and use them to improve compliance and trust in a given socio-economic infrastructure. The framework consists of three components: a law formalization process resulting in a normative system implemented as an agent-based model, a profit-driven agent generating instances of non-compliance, and a norm extraction process transforming the generated behavior into a formal model. Early research results of practical implementation of this methodology are illustrated on a multinational tax avoidance case. Towards the end, we focus on open issues related to behavior clustering and data/process mining.