# Conway's Reverse Game of Life 2020 — Data

来源：https://www.kaggle.com/competitions/conways-reverse-game-of-life-2020/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

We have provided 50,000 training games and 50,000 test games, whose starting board you must predict. Each board is 25x25, for a total of 625 cells per board. **Values are listed in a row-wise order.** You are free to create more training games if you desire.

The provided variables are:

* `id` - unique identifier of each game
* `delta` - the number of steps between the start and stop boards
* `start_0` - row 1, column 1 of the game's starting board
* `start_1` - row 1, column 2 of the game's starting board
* ...
* `stop_0` - row 1, column 1 of the game's stopping board
* ...

Your test-set predictions should be the starting board at delta steps before the stopping board. The games were created by the following procedure:

 1. An initial board was chosen by filling the board with a random density between 1% full (mostly zeros) and 99% full (mostly ones).
 2. This initial board was evolved 5 steps.
 3. The starting board's state was recorded after the 5 "warmup steps". These are the values in the start variables.
 4. The starting board was then evolved delta steps. Delta was chosen to be uniformly random between 1 and 5. If the stopping board was empty, the game was discarded.
 5. The stopping board's state was then recorded. These are the values in the stop variables.

## FAQs

* **Why the need for warmup steps?** The transition from an initial random board to the second step can be quite "nonlinear" and dramatic. For example, if a board is mostly alive at the first step, it will be mostly dead on the second. We allow the game to warmup for five steps in order to let the cells calm down and settle into a more "life-like" state.
* **The Game of Life loses information over time. What gives?** Correct, this is a many-to-one problem (many starting states can lead to the same stopping state). For example, many boards that are sparse at the start will end up in the same state (and you will see this in the data). However, over short time scales we expect this to be a minor issue. The largest step back in time in this competition is 5, which we hope is not so far that the degeneracy becomes an issue.
* **Can I predict any valid state?** Yes. Any starting state that achieves the ending state will achieve an optimal score.