This repository was forked and contributed to as part of a NUIG assignment which focuses on teaching python and other tools useful in the AI industry.
The goal of the assignment was to manualy solve three tasks from the ARC repository and include appropriate comments explaining how the results were achived.
All taks in ARC are different, each task requiring a slightly different approach. However once each task is broken down into individual steps it can be seen that most of the underlying tranformations and information gathering is the same across most of them.
In summary each solve() function can be built from a finite set of simpler operations on the pattern.
Based on the above a utility file was created containing some of the common tranformations. To make the common transformations reusable I developed the following representation of data.
- pattern - a list or a numpy array representing the input pattern from the json file as is, colour values positioned in order in a 2D space
- cell - a single cell represent a point from a pattern in the following format
(y, x, colour) - shape - a list consisting of unordered cells, is one dimensional and can have any size i.e
[cell1, cell2, cell5, cell6]
I developed a somewhat robust algorithm for finding shapes. It is based on a breadth first search algorithm (BFS) and allows for things such as ignoring certain colours or specifing a range for neighbours to be included in the search. The only thing it does not check for is diagonal neighbours, for the three selected tasks there was no such need.
This repository contains the ARC task data, as well as a browser-based interface for humans to try their hand at solving the tasks manually.
"ARC can be seen as a general artificial intelligence benchmark, as a program synthesis benchmark, or as a psychometric intelligence test. It is targeted at both humans and artificially intelligent systems that aim at emulating a human-like form of general fluid intelligence."
A complete description of the dataset, its goals, and its underlying logic, can be found in: The Measure of Intelligence.
As a reminder, a test-taker is said to solve a task when, upon seeing the task for the first time, they are able to produce the correct output grid for all test inputs in the task (this includes picking the dimensions of the output grid). For each test input, the test-taker is allowed 3 trials (this holds for all test-takers, either humans or AI).
The data directory contains two subdirectories:
data/training: contains the task files for training (400 tasks). Use these to prototype your algorithm or to train your algorithm to acquire ARC-relevant cognitive priors.data/evaluation: contains the task files for evaluation (400 tasks). Use these to evaluate your final algorithm. To ensure fair evaluation results, do not leak information from the evaluation set into your algorithm (e.g. by looking at the evaluation tasks yourself during development, or by repeatedly modifying an algorithm while using its evaluation score as feedback).
The tasks are stored in JSON format. Each task JSON file contains a dictionary with two fields:
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs)."test": test input/output pairs. It is a list of "pairs" (typically 1 pair).
A "pair" is a dictionary with two fields:
"input": the input "grid" for the pair."output": the output "grid" for the pair.
A "grid" is a rectangular matrix (list of lists) of integers between 0 and 9 (inclusive). The smallest possible grid size is 1x1 and the largest is 30x30.
When looking at a task, a test-taker has access to inputs & outputs of the demonstration pairs, plus the input(s) of the test pair(s). The goal is to construct the output grid(s) corresponding to the test input grid(s), using 3 trials for each test input. "Constructing the output grid" involves picking the height and width of the output grid, then filling each cell in the grid with a symbol (integer between 0 and 9, which are visualized as colors). Only exact solutions (all cells match the expected answer) can be said to be correct.
The testing interface is located at apps/testing_interface.html. Open it in a web browser (Chrome recommended). It will prompt you to select a task JSON file.
After loading a task, you will enter the test space, which looks like this:
On the left, you will see the input/output pairs demonstrating the nature of the task. In the middle, you will see the current test input grid. On the right, you will see the controls you can use to construct the corresponding output grid.
You have access to the following tools:
- Resize: input a grid size (e.g. "10x20" or "4x4") and click "Resize". This preserves existing grid content (in the top left corner).
- Copy from input: copy the input grid to the output grid. This is useful for tasks where the output consists of some modification of the input.
- Reset grid: fill the grid with 0s.
- Edit: select a color (symbol) from the color picking bar, then click on a cell to set its color.
- Select: click and drag on either the output grid or the input grid to select cells.
- After selecting cells on the output grid, you can select a color from the color picking to set the color of the selected cells. This is useful to draw solid rectangles or lines.
- After selecting cells on either the input grid or the output grid, you can press C to copy their content. After copying, you can select a cell on the output grid and press "V" to paste the copied content. You should select the cell in the top left corner of the zone you want to paste into.
- Floodfill: click on a cell from the output grid to color all connected cells to the selected color. "Connected cells" are contiguous cells with the same color.
When your output grid is ready, click the green "Submit!" button to check your answer. We do not enforce the 3-trials rule.
After you've obtained the correct answer for the current test input grid, you can switch to the next test input grid for the task using the "Next test input" button (if there is any available; most tasks only have one test input).
When you're done with a task, use the "load task" button to open a new task.