Modeling risk perception using independent and social learning: application to individuals with autism spectrum disorder.

The current study mathematically models key factors influencing Risk Perception (RP) that involves knowledge inferred from present situations and social learning, past information and priming effect. It is a generalized perception-based model and in the present paper, it is applied to Autism Spectrum Disorder (ASD). The computational model has been simulated for numerous rounds in two phases to find a quantitative value of the model factors. In the first phase, the model reflected dependency of RP upon recent past events and priming, while second phase revealed that social learning modulates RP, even in ASD. This further proves that peer-interaction plays a crucial role in building perception. Thus, our work provides a mathematical framework to evaluate perception objectively in any situation, such as risky/danger-situations. [ABSTRACT FROM AUTHOR]