Coming soon

Introduction

Simulations in HASH allow you to explore the real world in-silico, through agent-based models (ABMs). This approach improves upon historical Discrete Event (DE) and System Dynamics (SD) forms of simulation, leveraging the now-widespread availability of compute resources and granular data to simulate systems in high-fidelity. The underlying engine that powers simulation modeling in HASH (hEngine also supports running DE and SD models, but the traditional benefit these approaches offer of being "relatively simpler" is eliminated with HASH, which simplifies the process of building and using ABMs.

Agent-Based Modeling

In HASH ABMs, typed entities from a web can be instantatied as agents. Alternatively, synthetic populations of "lookalike" agents — of any arbitrary size — can be dynamically generated from example entities in a web, or user-provided descritpions.