The Ideation
13/07/2023 – 1545 hours
Okay so before I get into the details of everything, I decided to keep track of my progress through the projects I make on this website — a detailed, intricate progress which I can look back on and see how I made progress throughout the years.
First up, a website that solves a Rubik’s Cube in any state.
About the project
I sat on my couch around lunch time, and decided to open r/MachineLearning. Read about a long-time moderator deleting his reddit account due to the third-party tool nonsense that reddit decided to pull, and scrolled down.
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The stuff on there confounded me — as does AI & ML in general. Hence, I searched “for beginners” within the subreddit, which led me to another sub — r/learnmachinelearning, where I came across this AR model that sees the faces of an IRL cube and is able to solve it.
That basically was the basis of my idea — it is nothing new, I’m sure hundreds of such Rubik’s Cube solving sites exist — but none of them were made by me. This felt like something I’d love to try my hand at — a website where the user enters the configuration of their current cube, and the computer shows the user a step-by-step algorithm to solve the cube.
Learning & Research
Now how to solve a cube IRL is something I know, but how to write code to solve it? 0 clue. Hence, used my best friend Google again.
Turns out — there are around 43,252,003,274,489,856,000 combinations a Rubik’s Cube can have, so brute forcing my way through this was out of the question. Then I also came across this beautiful phenomenon, which actually left me quite astounded — the existence of a God’s number, that is the maximum number of moves required to solve any of the 43 quintillion combinations of a cube. And believe it or not, any cube can be solved within 20 moves. That’s it. Twenty.
I then spent some time reading this blog post — Building a Rubiks Cube Solver With Python 3. It gave me a very base understanding of what algorithm is being implemented to solve a cube in python — a ‘game tree’ approach, which is basically a graph representing all the possible states of the cube from it’s initial state to it’s solved state, and finding the shortest path from source to destination using the Iterative Deepening A* (IDA*) search algorithm. As of the date of this blog post, I have just finished my second semester of engineering, and I have learnt graphs in DSA (including BFS, DFS, Prim’s, Kruskal’s & Djikstra’s Algorithms), so even though IDA* did go majorly over my head, I also understood what it tried to achieve here.
This, though, wasn’t something I could implement on my own yet, but then I came across the Kociemba python library. Named after the famous cube explorer Herbert Kociemba (who also proved the God’s number), this library had a solve() function which took a string input of the cube’s current state and returned a string containing the moves to be performed to solve it. Simple.
