An Innovative Combination - The Spatial Poisson Process in an Agent-based Model

Presented by:
Xiaoli Yangi & Leshi Yang (University of Toronto)

In this presentation, an innovative combination of the spatial Poisson process and the complex system will be explored and discussed. In real research, the spatial Poisson process is usually used to compute the benchmark statistics compared to some unknown process. However, it reveals much greater potential in fields such as forestry and epidemiology when incorporated into COBWEB, a piece of agent-based simulation software that effectively replicates a system and predicts the interactions between the system components. This innovative combination can model completely random processes like the emergence of COVID-19 cases among self-isolated people after close contact with infectious sources, and the spread and adoption of new agricultural technologies within an area. What are some other potentials of this innovative combination? Were there any challenges when incorporating such an abstract process into an agent-based system in software implementation? What are the promising next steps to extend the influence of this result? We will walk you through all of these questions in this exciting presentation.