Objective Function

An objective function quantifies the performance of a system or algorithm, guiding its optimization towards a desired outcome. Current research focuses on improving objective function design and optimization across diverse applications, including machine learning (e.g., using gradient-based methods for multi-objective problems and novel acquisition functions in Bayesian optimization), robotics (e.g., goal-adaptive navigation and Pareto-optimal path planning), and causal inference (e.g., unit selection for optimal causal effects). These advancements enhance the efficiency and robustness of optimization algorithms, leading to improved performance in various fields and providing a deeper understanding of complex systems.