Towards a Computational Human Behavioral Model

This paper introduces a computational model capable of receiving human behavior patterns, extracting relations and generating new inferences and insights about targeted actors as well as predictions about expected patterns of behavior. Designing an abstract behavior model is the core problem being solved here to reach behavioral analysis goals such as relations extraction, insights generation and prediction. The level of abstraction is being achieved by defining abstract data structures that can receive, qualify and quantify behavioral information for a targeted person, as well as the definition of logical and mathematical relations among data structures using a set of logical and mathematical rules. Identifying data and logic elements properly leads to a behavioral model that can be the basis of any intelligent computer system understanding human behavior and responding according to human needs. Revolution in human-machine interfaces and sensory technology made any computer system capable of capturing natural human input. However, systems are still limited in how such input is interpreted.