Intelligent Furniture Placement using Reinforcement Learning

Designing a well-organized room layout plays a key role in making a space both practical and visually pleasing. However, deciding where to place each piece of furniture can be quite challenging, especially when dealing with many items. This project tackles that challenge by using reinforcement learning — a branch of artificial intelligence — to help find smart and efficient arrangements. We developed an intelligent agent that figures out how to place items like furniture in different room layouts. It learns by experimenting with various arrangements, receiving rewards for good decisions and penalties for less effective ones. Over time, through repeated trials, the agent identifies the optimal methods for arranging objects.