Hi! It's Monday, which means I'd rather write this log than code
Since our last encounter, I've been racking my brain on the 'final piece' of the flow economy: capital expenditure (in particular, the upgrading of existing assets and the acquisition of new ones). CapEx is necessary to make the economy grow. We already have a sturdy equilibrium; now we require a force to grow it out of the void.
I must admit, I have been underwhelmed by my search for algorithmic harmony here. I have not had breakthroughs or clever thoughts. That being said, I believe that this is partly because the right answer to the problem is not clever at all, but actually quite dumb. I am intentionally writing this log prematurely so that I may think through it more in words before I implement it.
This problem is, as I mentioned previously, quite difficult. To know the value of a new asset, one must theoretically be able to predict the impact of that asset on the global economy. In particular, one must (again, only theoretically -- in practice we will approach it very differently) be able to predict the impact upon all other agents in the system. Like a game of chess, much of the difficulty in deciding what to do with your turn (or in LT, your credits) lies in speculatively simulating the decisions of others.
The difficult only really manifests at large scales -- a critical fact that I will go on to exploit vigorously in subsequent paragraphs. If we're talking about acquiring a new fighter escort, a new mining vessel, etc. we can make some reasonable estimates about what's going to happen based on what's already happening. Such an asset is only a small 'perturbation' to the existing economic landscape, hence, we do not need to be concerned that adding a lone new ship to our fleet will upset the entire dynamical system and subsequently render our decision wasteful. The same goes for investing in upgrades to existing assets, which is, in practice, even easier: we invest in our most successful assets and divest of those that no longer justify their upkeep, e.g. upgrading our prized bounty fighter's weaponry, hiring an escort wing for a mining barge that has struck diamond, selling off an old battleship that hasn't seen action in a year, and so on.
Now, consider the construction of a generic trade station. Or of a factory. Or really any such 'large' asset. The situation is not so easy. By their nature, such assets have the potential to disrupt the whole of the local dynamics -- they are more than just perturbations! Following this line of thought and trying to solve the problem of "should I construct a trade station here" in an algorithmically/mathematically satisfying manner is a great way to drive oneself to madness and computational despair as the recursion unfolds before one's eyes But fear not: if stations were made of sand, perturbations would mollify all our angst.
Perturbative Quantum Flow Economics
(Look, sometimes I just want to sound fancy, alright?)
Chris Martin wrote:Oh but if you never try, you'll never know
Just what you're worth
Suppose that, instead of building a large trade station, you built a tiny one. Let's say, for the sake of discussion, that you built a single 'quantum' of trade station (although it's not important for this discussion, we could rigorously define such a quantum as, for example, the capacity to handle one transaction per unit time, or perhaps the capacity to handle the transaction of one unit of matter per unit of time, etc...). It would barely impact anyone. Barely.
However, if this capacity for handling transactions is valuable at the spatial location at which we placed our trade station quantum, then we will, in fact, see it being used. The AI is constantly looking for ways to optimize economic 'pressure,' as discussed in previous logs. If that transactional capability presents an opportunity to do so, then it will be used, despite being a small opportunity. We will see, for example, one miner choosing to drop off at our station instead of a further destination, and perhaps another AI ship choosing to trade between our station and another node in the economy (to balance the flow). We can then see, via flow measurement, that our station is being used! Thus, by introducing a differential change to the system, we have extracted a measurement of the change's differential value. And that's all we need
You see, by taking our purchase of a new asset into the domain of the quantum -- that is, by making the smallest change that it is possible to make to the system, what we have actually done is converted the problem of reasoning about a new asset into the problem of reasoning about an existing one, making the assumption that it is effectively 'free' to purchase a single quantum (minimal discrete unit) of any given asset (this assumption is important and I will probe it further later).
Now we will either kill off our micro-station, or grow it, based on the value measurement obtain from flow data. The algorithm for doing so is the same one that we will use to upgrade any other asset. Eventually, if we continue investing in our station, we will reach a critical point at which additional capacity for transactions will remain unused due to providing no further benefit to the system. Our station has thus reached adulthood and we may leave it be It is as though our little quantum station feeds on economic flow until it has reached the limit of its usefulness, at which point it ceases growth. It does not have to be a station; naturally this logic extends to any asset, although the trick of breaking down any given asset type into a single 'quantum' of sufficiently-small size is non-trivial.
But what if the station is in a suboptimal location? Sure, maybe it was viable to put it at X, but what if having put it at Y would have made everyone's life even easier? I claim that it doesn't matter! Here's the beauty: sooner or later, another perturbation will come along, and if it's better than our station, we will slowly-but-surely lose business to it. Sooner or later, optimality will be evolved naturally through competition. Even if our station wasn't optimal, it was good enough to survive, and that meant that it provided value to the system. That's all that matters. If a day comes when the system is so finely-tuned that the suboptimality of its location actually matters, a perturbation will come along and unseat it, eventually growing into the station that will replace it. Such is the nature of competitive evolution. A business that provides something fundamentally new has an easy time growing. It is only later, when adequate competition comes along, that the new market is pushed toward efficiency.
In summary: if you could make a minimally-small investment, it would be easy to invest; just invest in random things, and then grow or shrink your investment according to performance. As long as a 'minimally-small investment' is negligible in comparison to your wealth, you'll be ok. While I don't recommend this advice for real-world businesses, it is a simple and elegant technique well-suited to game AI.
Having heard the basics, there are now several good questions to be asking:
1. What does 'minimal discrete unit' look like for stations, ships, warp rails, etc? Can all assets be made granular?
2. What of the fact that it's not actually free to purchase things, no matter how small? Doesn't this necessitate thought in our 'random' investment, even for 'quantum'-sized ones?
3. Just because an investment is viable does not make it the best, or even close to the best, use of our money?
4. I don't want to see all of this clutter in the game world. I don't want to live in the same sandbox in which AI players are relentlessly experimenting with tiny, bad ideas.
1 is a question of design. It can be made to work, though it has implications that need to be carefully considered for, e.g., capital ships.
2 necessitates either a 'refund' for initial investments, or a 'good-enough' heuristic algorithm for suggesting them in the first place. It requires further thought, but such quasi-random suggestions (followed by more careful analysis) are already at the heart of much of the AI, so it would seem a natural fit.
3 is a non-issue for the same reason that the suboptimal positioning discussed above is a non-issue.
4, despite not being a question, is a little troublesome, but can mostly be waved away by saying "things in the prime of their growth aren't always pretty, it's the result that matters." Indeed, it's no problem if this wild experimentation happens mostly in the historical simulation phase. However, it is true that systems 'on the frontier' of developed space could end up a bit chaotic, and I'm mostly OK with that.
So, does it actually work?
Find out next time! It took an annoyingly-long time to convince myself that there is no simple, tractable solution other than "just try it." In the process, I managed to get myself tangled in a variety of other mechanics that I'm working out in parallel, namely, faction formation, faction goals, and AI algorithms for choosing faction alignment. I had suspected that factions were involved in the answer to capital expenditure, or at least had hoped that they would ease the burden, but so far they have not. Still, it's nice to have some faction theory happening at the same time. Never hurts to be thinking about the big picture.
In the coming week I will be exploring the behavior of systems that employ this granular approach to expansion without concerning myself with the questions enumerated above. First we will take a peek and see if the dynamics are nice. If so, we will use any means necessary to justify them and resolve the questions With luck, it should be a week of many baby quanta.
Once again, I will inform of any major breakthroughs if they occur this week, else I look forward to having something to show for this theory next week. I apologize for not being clever enough this time, but then again, sometimes it is quite clever to be stupid