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momom2

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AIS student, self-proclaimed aspiring rationalist, very fond of game theory.
"The only good description is a self-referential description, just like this one."

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momom2

AIS student, self-proclaimed aspiring rationalist, very fond of game theory.
"The only good description is a self-referential description, just like this one."

Top postsTop post

War of Dots: CRUSHING my opponents with FACTS and LOGIC

War of Dots is a free minimal RTS on Steam. The gameplay is simple enough to be described in its entirety in a blogpost, but I'm too lazy to do so, so I'll only consider what I need for my analysis. This article will describe the main mechanics identified to this day, and use maths to elaborate an effective strategy (with a brief discussion of real-game application). A winning manoeuver for red during a War of Dots match Introduction You control dots, which fight when in contact with enemy dots. Your goal is to capture cities (which provide funds to buy dots) and kill enemy dots. There is a mild snowball effect such that the game is usually decided by the time the first city (out of typically 5) switches sides, or an army controls ~20% more troops than the other. The main concepts to master to become an excellent War of Dots player are: * Micro: * Attack surface (taking micro-engagements with more units in the fight than the enemy, dealing more damage than you receive) * Defence (having units fight without moving, for a mild bonus at the very beginning of the game) * Terrain (positioning your units on favorable terrain, in the rare cases where it matters) * Meso: * Cycling (pulling injured units out of the fight, sending fresh troops in) * Encirclement (cutting off enemy units from any city's zone of influence, which deals extreme damage to them over time) * City-sniping (tactical actions to capture an enemy city) * Tactic techs (various tricks to gain a mild advantage in specific situations, such as regen-blocking or tail engulfment) * Macro: * Concentration of force (forcing fights where you have more units than the enemy to leverage a better attack surface) * Recruitment (choosing how to exchange funds for units, and tricks to generate more funds) The economy and combat are very slow, leaving ample time to think, such that by far the two most important mechanics are cycling (how to weave troops in and out of combat) and encirc

Cheat sheet of AI X-risk

Two arguments against longtermist thought experiments

What criterion would you use to select companies likely to cause AI doom?

War of Dots: CRUSHING my opponents with FACTS and LOGIC

War of Dots is a free minimal RTS on Steam. The gameplay is simple enough to be described in its entirety in a blogpost, but I'm too lazy to do so, so I'll only consider what I need for my analysis. This article will describe the main mechanics identified to...

Give my children minds

Kathy Mar wrote Give My Children Wings (recording from Quarks & Quests, originally from Songbird, 1982). It is a beautiful song about how we do not hope for hope, but would rather have the future actually be! Written for the space age, this song resonates with a disillusioned part of...

momom2's Shortform

Two arguments against longtermist thought experiments

Epistemic status: shower thoughts. I am currently going through the EA Introductory Course and we discussed two arguments against longtermism which I have not seen elsewhere. So goes a thought experiment: imagine you have toxic waste at hand, which you can process right now at the cost of 100 lives,...

Nov 2, 2024•15

Piling bounded arguments

TL;DR: A series of valid bounded arguments all arguing the same proposition can only provide as much evidence as that proposition at best, so even if it looks like they're piling up in favor of a higher point, they're only as good as the most central of them. Epistemic status:...

Sep 19, 2024•7

What criterion would you use to select companies likely to cause AI doom?

(Asking for a project which involves collecting data from the major AI companies.) Potential ideas found during a brainstorm: - Threshold on number of parameters of biggest model produced. - Threshold on number of money invested in AI research. - Threshold on revenue. We're looking for a criterion that is...

Jul 13, 2023•8

Cheat sheet of AI X-risk

This document was made as part of my internship at EffiSciences. Thanks to everyone who helped review it, in particular Charbel-Raphaël Segerie, Léo Dana, Jonathan Claybrough and Florent Berthet! Introduction Clarifying AI X-risk is a summary of a literature review of AI risk models by DeepMind that (among other things)...

Jun 29, 2023•19

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