I will be presenting an empirical exploration of using machine learning and evolutionary algorithms to automate chemical product design. Our study demonstrates how computational design can be controlled via hyper-parameters to generate solutions with desired features and has important implications for automating chemical product design.

In this presentation, we will cover what Agent-Based Social Simulation is, how it is different to standard optimisation tasks and the role Machine Learning and AI plays in these systems. We will also go over the history of Agent-Based Social Simulation and illustrate some of new and exciting fields that are using it such as Epidemiology, Disaster Management and Computational Archaeology. Lastly, we will take a look at some recent developments in the field and try to predict what will happen next.