Abstract:
The difficulty in selecting suitable skincare products, owing to various skin types and
conditions, is a considerable challenge for consumers. Conventional approaches frequently
depend on trial and error, resulting in possible negative effects such as acne exacerbation,
hyperpigmentation, or other serious skin disorders. The insufficient comprehension of the
effects of environmental factors, dietary practices, and ingredient interactions intensifies these issues. This project presents an AI-driven skincare recommendation system that evaluates skin type and problems, taking into account medical allergies, lifestyle decisions, and product compositions.
Multi-agent systems consist of multiple autonomous agents interacting and collaborating to
achieve complex goals. Each agent specializes in distinct tasks and independently contributes its expertise toward a shared objective. In such systems, agents communicate and coordinate their actions, enhancing efficiency, scalability, and adaptability. This decentralised approach allows for simultaneous processing of diverse information streams and problem-solving capabilities. Consequently, multi-agent systems are particularly effective for applications requiring real-time analysis, decision-making, and personalised recommendations, especially in dynamic and complex environments.
