Landmark Based Heuristic

Landmark-based heuristics leverage strategically chosen reference points ("landmarks") to efficiently solve complex problems across various domains. Current research focuses on optimizing landmark selection and placement, including developing novel algorithms to identify relevant landmarks even in data lacking readily apparent ones, and employing these landmarks for efficient data embedding and search. This approach significantly improves the speed and scalability of algorithms in tasks such as planning and network embedding, offering substantial advantages over traditional methods in handling large-scale datasets and complex problems. The resulting improvements in computational efficiency have implications for diverse fields, including robotics, computer vision, and graph analysis.