Lazy Search

Lazy search is a computational strategy that prioritizes efficiency by delaying or avoiding unnecessary computations, particularly in scenarios with expensive evaluations. Current research focuses on applying lazy search techniques to diverse problems, including motion planning (using algorithms like A* variants and probabilistic roadmaps), machine learning (optimizing training dynamics in neural networks and improving the efficiency of differentially private algorithms), and cybersecurity (augmenting penetration testing with large language models). These advancements offer significant potential for improving the speed and scalability of algorithms across various fields, leading to more efficient and resource-conscious solutions.