If you can read this, then you already know that the OPTIMAES site has been fixed. I took my attention elsewhere over the last year or so and somehow the links (including to CSS) got broken making the site an unreadable ruin.
Thanks to WebFaction support it’s back.
I’m not actively doing anything on OPTIMAES at the moment, but don’t forget us, because that’s normally the kind of thing I find myself saying before I suddenly get inspired to start work on a project again.
In the meantime, I wholeheartedly recommend you take a look at the Positive Money site. Not quite the same topic or stance as us. But extremely interesting. (Read their research.)
Money Mapping (via Exmosis)
Zby asks : why OPTIMAES assumes homogeneous societies where all agents play the same strategy, rather than mixed societies where different agents play different strategies. (And would seem to be more realistic.)
The main reason for this at the moment is that it’s hard to see how different agent strategies would interact. Any kind of transaction is a property of a dyad (pair) that needs both to play their appropriate parts.
What would happen if a Gifting agent met a Barter agent? They’d end up having to adopt the same strategy if they were to successfully interact.
So, another move.
OPTIMAES has now left Ning for this WordPress blog.
True, I haven’t been doing much on OPTIMAES in the last couple of years, but it should at least have a decent home. Ning turned out to be flooded with spam. And now they plan to start charging. (I’m not against that per se, but I’m already paying for this hosting so might as well use it.)
Note, that I’ve tried to import blog posts from the old Blogger site and the Ning group. Unfortunately I seem to have lost dates on some of them so I’ve pretty much chosen arbitrary dates that suit the ordering I’d like to give the posts. Hope this isn’t too confusing.
Previously, the OPTIMAES experiment was being run, starting with 100 agents, on a grid. The grid constrains the agents so that each has only four neighbours with which they can interact. This gives relatively few opportunities for bartering or gifting. So few that bartering appeared to produce an effect that was little different from selfish isolation.
Did this mean that barter was wholly useless? Or that there was simply a bug?
To look more closely, the results of all three strategies (selfish isolationism, gifting and barter) were run in a fully connected world (ie. a world where all agents have each other as neighbour). That gives every agent 99 possible partners for gifting or bartering rather than 4.
All other parameters were kept the same. There are still 100 agents in the population and 3 resources. Although this time there are 30 rather than 10 runs of each simulation. The results shown are still the average.
What we see is that, for both barter and gifting, being fully connected seems to have a far greater impact than the strategy itself. While in both worlds, gifting does far better than barter. Both barter and gifting in the fully connected world perform better than either barter or gifting in the narrowly localized cases.
I added the “barter” agent to the preceding experiment.
Barter agents use a very naive bartering algorithm whereby agents attempt to swap what they need for what they have a surplus of … with neighbours who have opposite requirements. (See code here.)
The result :
And you can see that bartering ends up indistinguishable from selfish foraging.
For this reason, I’m not entirely sure about this yet. It looks so bad that I think there may be a bug in the code. I’ll try to let you know tomorrow. (All eyeballs welcome to have a look in the meantime.)
Alternatively I guess it could be that opportunities for bartering are so rare that they have no visible effect.
Hi to the people who just joined. If you didn’t notice the link, the OPTIMAES codebase is hosted on here on GitHub.
It’s in Python, and is a more or less complete rewrite. Currently we have selfish foragers, barter agents and gift-givers. I’m working on a new money-using agent, but haven’t yet decided the right algorithm. All suggestions are welcome.
Hi to Dante who’s just joined us. And thanks for adding us to the P2P Foundation’s Complementary Currency Software wiki page : http://p2pfoundation.net/Complementary_Currency_Software (…)
Interesting model of how recommendation systems reduce diversity and choice in a market. (…)
I got curious looking at the last results … does the population decline continue or does it bottom out?
Intuitively you’d think that it will bottom out somewhere because there is a sub-population who are self-sufficient (ie. for all resources, they can get more than they consume).
Does the gift economy eventually decay to the same level or can it sustain itself somewhere above that?
Here’s the same experiment run for 1000 time-steps. (As before you’re seeing an aggregate of 10 runs of a population that starts with 100 agents and declines to something around 20 to 30 … it *looks* like 1000 because of some quirks I encountered with decimals in the spreadsheet so I scaled up by x10 to whole numbers).
As you can see, although the gift-economy sustains itself for longer than the selfish foragers, it does also decline. This might be because there is still some randomness in the way the simulation works.
At each time-step, a random agent is chosen to forage, consume and optionally donate its surplus to needy neighbours. But it’s possible that for some needy, but unlucky, agents, their neighbours are never chosen and so never donate. Donation is not systematic as it was in earlier versions of OPTIMAES.
It remains to be seen if the decline of the gift economy will eventually fall to selfish forager levels.