Objective

This AI in Urbanism is to develop an agent-based reinforcement learning model, to understand how supply and demand for a particular functional type of floating infrastructure are managed.

With different numbers of starting locations and their corresponding results.

This trained model can be adapted to other scenarios and conditions to test the agent’s behavior.

Frequencity – Reinforcement learning is a project of IAAC, Institute for Advanced Architecture of Catalonia developed at Master in City & Technology in 2021/22 by student: Sridhar Subramani and faculty: Angelos Chronis, Nariddh Khean, Serjoscha Duering.