Machine Learning: Episode I

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Machine Learning: Episode I

Short description

Machine Learning: Episode is a first person arcade puzzle game built for HTC Vive. You play as an A.I. robot created in DARPA laboratory in the near future. One of the scientists is here to test your physical, perception and cognitive skills. By using the power of room-scale VR and Vive controllers

Developer
Volens Nolens Games
Publisher
Volens Nolens Games
Release
Sat, Sep 10, 2016
Price
$4.99
Reviews
66
Positive
83%
Followers
n/a
Owners (estimated)
20K – 50K
Concurrent players
1
Genres
Action, Adventure, Indie
Features
Tracked Controller Support, VR Only, Steam Trading Cards
Tags
Action Adventure Indie VR
Revenue (estimated, gross)~$6ksomewhere between $3k and $101k · roughly 1K–50K copies

Review count and SteamSpy's owner range disagree, so the band is widened to cover both rather than picking a favourite. Multiplied by $2.01, the average price these copies actually sold for — weighted from the price history rather than taken from the $4.99 launch price. That is 60% below list price on average. Before Steam's cut, VAT and refunds. How these numbers are calculated.

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History

3 data points since Aug 1, 2026. Gaps mean nothing changed — the value carries forward.

Revenue (est.) ~$6k → ~$6k
Reviews 66 → 66
Price $4.99 → $4.99
Positive reviews 83.3% → 83.3%

The revenue curve is an estimate, not a measurement. It is the only calculated series here: each interval takes the review growth of that period, multiplies it by the sales-per-review factor and by the price actually charged at the time, and adds the result to the running total. That is why it climbs more slowly through discount periods than the review curve next to it. The last point is the same figure quoted above — gross, before Steam's cut, VAT and refunds. How these numbers are calculated.

The blurred area is the rest of the history. 163 further data points reach back to Sep 1, 2016 — your plan shows the last 90 days of it. How far each series in particular reaches is written on its own chart; not every one of them goes back that far. The shape in the blurred area is decoration, not data: the figures are not in this page at all. Plus unlocks the complete series.

Lowest recorded price: $0.28 on Nov 22, 2022.

How crowded is this niche?

How full the niche around Machine Learning: Episode I is — measured on the tags it leads with, against every other combination on Steam.

±?? Action + Adventure + Indie

Combinations under 15 games are left out to reduce the influence of small samples. The games below share those tags and are free to browse.

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Similar games that found an audience

Games sharing at least 3 of this title's leading tags, with enough reviews to have gone somewhere. Ranked by how much they overlap, not by how big they are. − missing and + extra mark the tags each one does not share with Machine Learning: Episode I. Studio counts the titles that developer has released — the closest thing to production scale that public data allows. It is not a budget, and nobody publishes those.

Image Name Studio Shared Tag difference Price Reviews Positive Released Revenue (estimated)
Trover Saves the Universe Trover Saves the Universe Squanch Games, Inc. 4 titles 4 + Comedy + Dark Humor $29.99 2,800 91% Tue, Jun 04, 2019 $2.8m
$1.5m – $2.8m
Vertigo Remastered Vertigo Remastered Zach Tsiakalis-Brown 3 titles +2 4 + Gore + Violent $19.99 1,322 93% Tue, Jul 21, 2020 $961k
$508k – $961k
Budget Cuts 2: Mission Insolvency Budget Cuts 2: Mission Insolvency Fast Travel Games 15 titles +1 4 + Stealth + Singleplayer $14.99 461 82% Thu, Dec 12, 2019 $295k
$136k – $295k
Trickster VR: Co-op Dungeon Crawler Trickster VR: Co-op Dungeon Crawler Superstatic 2 titles 4 + Dungeon Crawler + Co-op $12.99 428 86% Tue, Jan 15, 2019 $228k
$101k – $1.2m
Island 359 Island 359 CloudGate Studio, Inc. first game 4 + Dinosaurs + Early Access $14.99 421 75% Mon, Feb 26, 2018 $297k
$297k – $499k

There are more like this. Your plan shows the 5 closest neighbours; Plus and Pro show up to 100 — enough to see the shape of a niche instead of a sample of it.

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