Fractal AI goes public!

Today we are glad to announce that we are finally releasing the "Fractal AI" artificial intelligence framework to the public!

This first release includes:

• Fractal AI: A fragile theory of intelligence A nice to read small book in PDF with theory, algorithm, pseudo-code, experiments, etc.
• github.com/FragileTheory/FractalAI with working python code to beat almost all of the actual Atari games.
• Tons of videos showing Fractal AI at work, along with some talks, etc.

We have modified Fractal AI a little so now it is more powerful than ever, in fact we have been able to beat a lot of the actual records (from state-of-the-art neural network like DQN or A3C) with about 1000 samples per strep (and remember, no learning, no adaptation to any game, same code for all of them).

We are specially proud of beating even some absolute human world records, but hey, it was going to happen anyhow!

Fractal AI playing Ms Packman. It reached an unknow score limit of 999,999 present in a total of 15 games. Fractal AI beated the best human records in 49 out of 50 games.

Solved atari games

The list of environments from OpenAI that we have already played so far is steadily growing, so I had to made a list to keep track of them. Here we keep and share this growing list, along with it scorings and how it compares with the "second-best" algorithm in the OpenAI gym.

For the interested people: We base all on our work on the "Causal Entropic Forces" by Alexander Wissner-Gross and apply the ideas outlined in the G.A.S. algorithm. We are not actually learning in any way, so all games are independent from each other and first-ever played game is as godd as the 100th game.

First, we list the already finished environments. They include 100 games played and an official scoring in OpenAI gym as the average of those 100 games:

1. Atari - MsPacman-ram-v0: average score of 11.5k vs 9.1k (x1.2)

This was the first env. to be finished and uploaded, so it represent our first official record. We decided to use the "ram" version (instead of the image version) because it is irrelevant for our algorithm but not for a more standard approach, so we had an extra punch.

The main issue here was a dead Pacman takes about 15 frames to be noticeable on screen (there is a short animation) so you need to think in advance at least those 15 frames (ticks) in order to start detecting death.

OpenAI first record!

We have just submitted our first official scoring on OpenAI gym for the atari game "MsPackMan-ram-v0" based on RAM (so you do not see the screen image, instead you "see" a 128 KB RAM dump).

Our just submitted algorithm "Fractal AI" played 100 consecutive games -the minimum allowed for an official scoring- and get an average score for the best 10 games of 11543 +/- 492, well above previous record of  9106 +/- 143, so we are actually #1 on this particular atari game:

Fractal VS Pack-Man

Last week my friend Guillem adapted the fractal AI for the OpenAI Atari games (OpenAI is a "gym" for AIs), in particular he focused on "Ms Pack Man", an environment labeled as "unsolved" as I write this.

Yesterday the work was almost done and the first videos came out of the pipeline and, to be honest, the results have stonished me, it worked out far beyond my always-optimistic high spectations.

So here is the video that made me so happy yesterday: