Abstract
This proposed system introduces a dynamic coupon generation mechanism empowered by machine learning algorithms, particularly reinforcement learning, to enhance people's engagement and optimize coupon distribution in such a way that the coupon for the subsidy is given to farmers fairly by prioritizing those in need. This process involves key stages, including data gathering, preprocessing, feature enhancement, and autonomous decision-making logic development, taking into account diverse factors such as farmer segments and budget constraints. The system interacts with HTML, PHP, CSS, and JavaScript, with Python supporting the implementation. This paper aims to continuously adapt the model to meet evolving customer behaviors and preferences. This technological approach is essential for optimizing coupons effectively and staying responsive to real-time customer interactions and preferences.
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