The speed advantages of PFN-based BO can be leveraged to enable user-guided interactive optimization and adaptive experiment design in engineering applications through the following approaches:
Real-Time Feedback: The fast optimization process of PFN-based BO allows for real-time feedback to users during the optimization process. Users can interactively guide the optimization by providing feedback on the current solutions and influencing the search direction.
Dynamic Experiment Design: PFN-based BO can adaptively design experiments based on user inputs and feedback. The speed of the optimization process enables quick adjustments to the experimental setup, allowing for dynamic changes based on user preferences or constraints.
Interactive Visualization: Utilizing interactive visualization tools, users can explore the optimization process in real-time, visualize the search space, and interact with the optimization algorithm to steer it towards desired solutions.
User-Defined Objectives: Users can define custom objectives or constraints interactively, and the PFN-based BO framework can quickly adapt the search to incorporate these user-defined criteria.
By integrating these features, PFN-based BO can facilitate user-guided interactive optimization and adaptive experiment design in engineering applications, providing a flexible and efficient platform for solving complex optimization challenges.