MarI/O - Machine Learning for Video Games

OP, Togelius, is quite wrong in 1 point at least. tl;dr Seth Bling directly references NEAT and his links[Show More [1]] link to 2 Togelius papers[13][14] among many others ! To wit, in OP, Togelius mentions Seth Bling's MarI/O[1] as lacking scholarship because he didn't mention Togelius: " seen as research, it is atrocious because of the complete lack of scholarship. The guy didn't even know he was reinventing the wheel, and didn't care to look it up. " Rather disdaignfully (sadly/ ironically/ poigniantly) Togelius refers to Seth not by name but only as " some guy ". Yet Seth Bling[2] in his short video, mentions and explains NEAT and directly links Ken Stanley's and Risto Miikkulainen's foundational NEAT paper[10] at U.texas which Togelius builds on [hint: click SHOW MORE under Seth's video] And much more, i.e.: ---- the innovative toolchain Seth uses: Bizhawk to script SNES emulators in Lua [12]! ---- Seth links the wikipedia page on Neuroevolution[11] which directly references 2 of Togelius's own papers[13][14] Seth's [Show More] Links on the MarI/O video[1] are very very comprehensive and (IMHO) indeed a great example of scholarship ! Togelius is a top flight scholar, and publishes in the field of AI game players and level generators[15] so I hope he will welcome some random tinkerer pointing out his error. [full disclosure: I am a Togelius fan] To give Togelius his due he does at least link to Seth's MarI/O video. Perhaps Togelius failed to click / read the Show More li

I'm a novice at machine learning, but Open AI made a python library for reinforcement learning in video games, and a fork of it is still actively maintained [1]. It's been a few years, but I remember being able to get it up and running in a day or two (maybe a weekend). It used the Retroarch emulator, which is compatible with a huge number of emulators and consoles. [LINK] There also SethBling's excellent video on YouTube about machine learning specifically with Super Mario World: [VIDEO] I encourage you to give it a try! I feel that video games are a bit underrated by current AI buzz, I think there's lots of potential for a machine to learn a skill through playing a game. And lots of potential for a game being selected or even created with the goal of teaching a specific skill. However at that point maybe it's better to forego the audio and visuals and speak to the machine in text or with pure data. On the other hand, I have seen a video about convolutional neural networks that feed on each pixel of an image. So perhaps training with sound data, or with the pixels of a spectrogram, could have some positive results. And certainly I would be amused to see a game played in time with music, or possibly even dancing with a songs melody, harmony, and story as well. Anything that's ever been created by humans, existed first in the imagination of a human brain. And you've got one of those. A mental vision pursued and brought from the mind into physical reality is a beautiful thing,

Here is my favorite introduction to NEAT: SethBling's MarI/O - Machine Learning for Video Games [VIDEO]

I believe it's been posted before, but sethbling (of vanilla-minecraft-hacks fame) pulled off the impossible and did the credit warp on an actual SNES, live[1]. As this video very-nicely explains, this required incredible amounts of pixel-perfect accuracy. Lining up the line of koopa shells on exact x-offsets and very narrow heights mid jump (!) to write the landing-sled - using a controller, realtime - is utterly insane. As a side note sethbling's latest project is teaching[2] (using neuro-evolution) his machine learning bot to play SMW[2], SMB1[3], and Mario Kart (original)[4]. While he machine learning is simple by today's standards, his brief videos give a really nice introduction to the topic that should be accessible to most people. [1] [LINK] [2] [VIDEO] [3] [LINK] [4] [LINK]

There is an objective, but it may not be exactly as you reason about it. There's a great video that made the rounds last year about building a neural net that plays Super Mario World, that may help visualize what's going on - [VIDEO] There's also a great snippet in the currently-ongoing AlphaGo videos that explains that when AlphaGo plays in ways that you may not expect, it's because it's strictly worried about _winning_ (even by the slimmest margin) with the greatest probability, and not necessarily by winning handily, like a human might.

You mean this script? Or machine learning in general? If the later then it has already been done: [VIDEO] (great educational video)

This video of a Super Mario playing AI was pretty neat: [VIDEO] It may, or may not be on a useful path to solving harder AI problems. I don't know. But it's a good way of demonstrating value (and publishing papers).

Neuroevolution of Augmenting Topologies is a classic genetic algorithm, as a teenager it was my first genetic algorithm I implemented after watching a Youtube video of an implementation of it - [VIDEO]