Face Connected Cube

Research on "face-connected cubes," often exemplified by the Rubik's Cube, explores efficient algorithms for solving complex manipulation and optimization problems. Current work focuses on applying graph-based representations and advanced search algorithms like A*, along with machine learning techniques such as reinforcement learning and convolutional neural networks, to find optimal solutions and improve the speed and efficiency of solving these puzzles. This research contributes to broader fields like robotics (manipulation benchmarks), optimization (non-convex function minimization), and AI (planning and learning), offering insights into efficient problem-solving strategies and the development of robust, adaptable algorithms.