Intelligent Furniture Placement using Reinforcement Learning

Aryan Parekh, Soham Patil, Yash Kulkarni, Krish Panchal and Rohini Nair

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 4, 224-231

Abstract: 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.

Keywords: Reinforcement Learning (RL); Intelligent Agents; Reward function; Spatial optimization (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2511159
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i4:id:1609

DOI: 10.32628/CSEIT2511159

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