>we do need and should have good fine-grain computational models of complex systems such [...] the global economy.

Many years ago when 'social graphs' were still a hot area to do research in I started building a simulation of the equivalent of a small medieval village.

What became quickly apparent is that you didn't just need interactions between any two individuals like classical social graphs talked about, but between any number of arbitrary groups of individuals. Otherwise something as simple as an extended family couldn't be modeled.

That meant that instead of being able to use a matrix as the fundamental data structure you'd need a tensor of rank N, where N is the number of people in the economy. Just to see how intractable this is if the village had 20 people in it with the traditional matrix approach you'd need 400 weights to model interactions. With the tensor approach you need ~1e+26.

In short: it's impossible to have fined grained simulations of complex societies. The best we can do is drastic over simplifications that give us _some_ predictive power.

There’s a whole discipline which does nearly that, though they do not use this style of agent based model.

Generally agent based models have numerous parameters which can take many values (endowments, preferences) and the models don’t themselves give any guidance about how to set the parameters. Theory can give limited guidance (eg., that function is concave, this parameter is negative). Sometimes we have experimental data though its generalizability beyond the lab is uncertain.

What you want to do to create a scientific macroeconomics is to work backwards from the data you see in the economy (aggregate consumption, investment, etc.) and how you know the aggregates were generated (via the behavior of a lot of individual agents), and an equilibrium assumption to recover the parameters.

If you know the parameters of the model you assume, you can then simulate interesting counterfactuals. (And yes you assume the model - a “full” model including “all” of the individual endowments and parameters you can think of is completely intractable. You have to simplify.)

You’ll never get that out of the author’s computer game.

If you want references to the macro literature it’s enormous and I can provide them.

We already have tons of those models.

None of them are perfect.

And they never will be.

Could the be better? Yes.

The problem is, you won't really know they're better until post-ex. And even then, you'll never be sure how much better. They're always bound to fail catastrophically at some point. Etc.

You've stumbled upon Chaos Theory (https://en.m.wikipedia.org/wiki/Chaos_theory), which aims to study chaotic systems (charactesised by very high relation to initial variables - see weather prediction, double pendulum, etc).

Some problems are too sensible to initial variables and solutions are not prescriptive like regular physics - meaning that variability at the 20th decimal in your initial variables will induce massive output differences. Lorentz discovery of this is interesting as he was working on weather modelling, it's a clear example of the issues with chaotic systems. He was running simulations of weather systems with multiple fixed initial variables (temperature, wind speed, etc) and seeing how the system progressed over a few hours. He realised that after a typo on a very far away decimal on a single parameter, the system was modelling the complete opposite of what we had seen in the previous test (think it was forecasting a typhoon when it used to say sunny day), even while using values that would be "equal" with relation to the precision of the measuring equipement. And that's nothing to talk about getting clean, precise enough data for such models, which is practically impossible (see the observer effect, between other causes). Garbage in, garbage out.

All this to say that problems in this sphere are characterized by quickly becoming untractable and impossible to model precisely how they evolve over time.

I can recommend James Gleick's Chaos: Making a new science for a overview for the layperson.

> we do need and should have good fine-grain computational models of complex systems such as the cell .. and the global economy.

Thanks to the pioneering work done by physicists, we realized we could simulate dimension reduced versions of reality instead. We call them statistics and differential equations :)

Stack enough of them together, you get something called "deep learning". Large scale national lab supercomputer type numerical simulations are for your grandparents (these days you can probably take shortcuts and simulate that sort of born secret computations in a neural net that is much more compute efficient than the typical supercomputer).

While your last point is certainly an ideal to aspire to, something tells me that the powers that be would not actually want to get rid of booms and busts, because ultimately that is where a lot of the “wealth” for those high up is created. You don’t really need complex models to solve the problem of some humans being really, really greedy, driving markets to overheat, ending in catastrophic failure.

Issue of the Commons.

Weather models are good because if we know about it the weather doesn't care and doesn't change what it is going to do.

Anyone who has an accurate financial model is keeping it to themselves.

Anyone who has an accurate financial model and make it public... invalidates their model as everyone takes that information and plans to take advantage of it accordingly.

If you had such a model you could arbitrage between Polymarket betting on wars and stock prices. There's not much of an incentive to release such a model publicly.

This opinion is hopelessly based in magical thinking not taking into account many things which have been well established since the early 1900s.

Its mindless garbage like this that fuels the waste, and other great delusions held by the public today.

Value is Subjective. That means it changes for each person, in each circumstance.

Ordinals != Math. They are inequalities at best. You can never prove X = Y with just X < Y.

Computation, absent a few niche areas require problems to be formulated deterministically. That means a unique set of inputs, and a unique set of outputs. If you get an input that has two hidden underlying states, this fails.

The environment of this problem domain is a stochastic environment, that means chaotic; mathematically.

It cannot be measured in any detail except in retrospect as a lagging indicator, and it neglects psychological aspects, and the resulting dynamics that prey on people when money printing is used (i.e. fiat currency).

> Of course this would require something like a rich country providing grants ....

There is no amount of grant money in the world that can do what you claim, it matters not that it is 1 year, 10, or even given over 1000 years. The underlying laws don't change.

The economic boom bust cycle causes are well known and documented in banking. People just don't want to listen to experts, and evil bankers have a vested interest in discrediting those that would speak out.

Being complacent, mistaking your average dunning kruger for an expert in an echo chamber, that's the level of thinking today for the vast majority of people, and I don't see this post as being any different. Three books is all you'd need to read to know about all of this.

The bust part of the cycle is the objective shortfall between productive labor and unproductive labor as losses get marked down. In other words if you loan out money to people whose intention and ability are not production, but instead fraud or other snake oil, then you have these happen. What goes up, must come down.

Inflating the currency with an exponential amount of money printed calling it liquidity, will stave off the issue for another 8-10 years or so, with diminishing returns each time and there is a hard limit based in the fundamental requirements for an economy to operate, going back to 1776 Wealth of Nations.

Producers must make a profit to continue operating. Labor providers must be paid sufficiently to support their needs, and the needs of a Wife, and 3 children; sufficient for 1 to live to have children themselves.

The latter is dependent on the former. The money spent by each party travels in a circle unless something breaks that balance. If that happens it stalls, money loses its fundamental properties (when its fiat), and with population above a certain scale you may get socio-economic collapse, which is a slow circling the drain chaotically.

Prior to the 1970s the gold and precious metals safeguarded society from going off the rails in giving money to people who instead of producing something just enriched themselves. Every time fiat was tried, by either fractional reserve with poor regulation, or no fractional reserve at all (as we have a/o 2020), it has failed. Coolidge walking back banking, and not bailing the banks out is what led to the Great Depression.

Productive activity fell because farmers couldn't plant their crops because loans weren't available; the rural banks overextended themselves and went bottom up. It contagioned all the way culiminating the the Wall Street crash, and the socialism that followed only made it worse.

Today the GSIBs are in the same situation, with no one to bail them out.

I'd highly suggest you actually do something about correcting the shortfall in education, much of this you should know by middle school if you received a proper education.

The funniest thing is that d2jsp was originally the forum of a bot developer.

Looks like bot runners where the one the most in need of a currency to make trades more efficient.

its really hard to make something like that fun. The real world economy is driven on asymmetrical inefficiencies and lack of information, things that wikis and game balance pretty much destroy.

It's only fun to make money on say world of warcraft because most people aren't also doing that. (but instead buy your goods and use them for something essentially unproductive in economy-terms) Even then it can feel pretty stupid given the amount of arbitrage bots people have set up, you have to focus on very niche opportunities or oversights by those arbitrage bots. Kinda like the real economy

Eve Online?

I love Primer, but this particular video has a fatal flaw which makes it converge to the same result as microeconomics: it considers seller's cost to be a marginal cost, which is zero when the rocket hasn't been sold and is paid when the rocket is sold. But that's absolutely not how real world market works, and a multi-agent simulation which has the ability to use different hypothesis (upfront costs) should definitely do so, because then we'd see a completely different result.

Looks like pure ebiten. https://github.com/JasonFantl/Simulated-Economy-Tutorial/blo...

Neural network based computer vision models also existed for decades. They weren't very good and weren't really used, till early 2010s when people figured out how to make them work. Now they are vastly superior to all the other ways.

This is quite common across the sciences. Some technique doesn't seem to work because of missing crucial insights or technology. Then somebody fills the gaps, and the technique works.

These types of models in economics might or might not become viable at some point.

You're taking this from the perspective of people who are stuck in a specific mental framework who want to prove that their mental framework is the right one, no matter how impossible it is in practice.

What if you don't care about tuning against a real macro-economy? What if the economy being fictional was the entire point?

Let's suppose you wanted to make a game that simulates a realistic economy as a gameplay element no different from say a physics engine. Why wouldn't you do it using agent based modeling? What you're saying sounds purely dogmatic now. It's more about thought termination than actually accomplishing something. After all, central banks and businesses don't give a damn that agent X did action Y at time Z for all agents, actions and times. Meanwhile in a game? It's actually essential, because the model is the reality inside that fictional world. The model is "perfect".

Sure, they've tried but it does not mean it hasn't evolved

https://www.centralbanking.com/central-banks/economics/macro...

https://www.bankofengland.co.uk/working-paper/2025/agent-bas...

Right, Agent-based models are only useful as “exploration” tool, you cannot really use them for forecast because there's an impractically high number of parameter to tune.

Micro-founded macro economics models (say DSGE) are much easier to tune based on available historical data so they are much preferred, and nobody seams to care that they have the same predicting power as astrology.

Demis Hassabis seems to describe a process whereby an AI can accelerate the results of billions of simulations by efficiently encoding that predictive behavior.. making something that is computationally expensive to simulate perhaps several orders of magnitude more tractable.

This has proven out in the acceleration of actual weather prediction using AI which means it can be feasibly run on a single desktop machine.

I think its not a stretch to imagine that a) there is a way to simulate the whole economy at the same level of quality as a weather or climate simulation b) AI can accelerate the computations to the point they can run on accessible hardware.

We need this whole economy simulation ... to answer practical questions such as - if we dole out UBI to everyone to cover basic living costs, will that simply result in the cost of rent going up to absorb the whole amount ?

Agent-based models capture the messy reality of economic systems by simulating heterogeneous actors making local decisions with imperfect information, allowing for emergent phenomena, non-linear dynamics, and adaptation over time, precisely the features that equilibrium models abstract away through unrealistic assumptions of perfect rationality, homogeneity, and static optimization that fail to predict or explain crises, bubbles, and technological disruptions that define actual economic evolution. To be honest, ABMs aren't perfect either. They face challenges with calibration, validation against empirical data, computational limitations, etc.