Alcohol-related problems (assaults, accidents and/or crimes) and alcohol abuse are recurrent societal problems leading to high social costs. Finding adapted policies to tackle this issue isn't a trivial task due to the highly complex nature of alcohol consumption as many interrelated risk factors interact in a hardly predictable way. This paper describes an agent-based simulation model, called SimARC (Simulation of Alcohol-Related Consequences), aiming at exploring the complex interplay of

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... factors following a generative process whereby theory and model co-evolve within iterative loops. To explore the complexity of alcohol use and abuse, we need not only to include the aforementioned risk factors but also their evolution and highly dynamical interactions across scales. Therefore, our agent-based model aims to encapsulate several levels of reality. Considering an ontology as catalog of elements and relation amongst those elements, our ontology-driven behavioral model includes: neuro-biological responses to alcohol use (individual level), peer influence channeled through various social networks (meso-level) and societal responses to alcohol-related problems (meta-level). This ontological framework aims to establish a robust test-bed to analyze-in silico-the plausible consequences of various public policies related to alcohol abuse in public venues. After a brief review of the literature, we present SimARC's core structure and preliminary results.