[FRIAM] Oblivion resistant swarm
Frank Wimberly
wimberly3 at gmail.com
Sat Jun 6 17:12:36 EDT 2020
Well, I had taught those optimization techniques at the master's level and
would have realized it if they were straightforwardly applicable to the
problem. Regardless, the extensions I mentioned were very easy to
implement given the existence of the basic ABM.
It was amazing to me that certain managers jealously guarded access to
their datasets and would not give them to us without a difficult
negotiation even though we were helping them in ways that their executives
had asked us to do.
Stephen, were you involved in any of this?
Frank
---
Frank C. Wimberly
140 Calle Ojo Feliz,
Santa Fe, NM 87505
505 670-9918
Santa Fe, NM
On Sat, Jun 6, 2020, 2:39 PM Marcus Daniels <marcus at snoutfarm.com> wrote:
> I would not go so far as saying *analytically*, but certainly if the
> simulation is computationally shallow – doesn’t evolve opportunity costs
> that need to unfold in time and space -- I would think mixed integer linear
> programming or constraint/logic optimization would give a more
> comprehensive result.
>
>
>
> *From: *Friam <friam-bounces at redfish.com> on behalf of Frank Wimberly <
> wimberly3 at gmail.com>
> *Reply-To: *The Friday Morning Applied Complexity Coffee Group <
> friam at redfish.com>
> *Date: *Saturday, June 6, 2020 at 1:17 PM
> *To: *The Friday Morning Applied Complexity Coffee Group <
> friam at redfish.com>
> *Subject: *Re: [FRIAM] Oblivion resistant swarm
>
>
>
> I thought it worked well. I don't know what Ford did with it if
> anythinng. There was at least one person that claimed he could reach the
> same conclusions analytically. But he wouldn't have been able to model the
> social interaction of customers, the effects of advertising, and the
> effects of social media for instance. I'll bet there are Ford Ranger
> Facebook groups. Ford wanted the results in order to determine which
> option sets to manufacture.
>
>
>
> Frank
>
>
>
> On Sat, Jun 6, 2020 at 2:12 PM Barry MacKichan <
> barry.mackichan at mackichan.com> wrote:
>
> How did it work out? Did anyone at Ford run with it?
>
> On 6 Jun 2020, at 16:08, Frank Wimberly wrote:
>
> I developed some ABMs at BiosGroup. That looks interesting and it would
> be fun to develop. The "Ford Model" that I implemented took more than two
> weeks and it was written in Java. If had to do with modeling purchaser
> behavior in relation to Ford Ranger pickups and the desirability of options
> sets. We were anticipating modeling the influence customers have on
> each other among other things.
>
>
>
> Frank
>
>
>
>
>
>
>
> On Sat, Jun 6, 2020 at 2:03 PM Jochen Fromm <jofr at cas-group.net> wrote:
>
> Looks interesting but complicated, I was hoping that Stephen or Owen might
> have seen something similar because they have done a lot of agent-based
> modeling as far as I know.
>
>
>
> -J.
>
>
>
> -------- Original message --------
>
> From: Marcus Daniels <marcus at snoutfarm.com>
>
> Date: 6/6/20 21:56 (GMT+01:00)
>
> To: The Friday Morning Applied Complexity Coffee Group <Friam at redfish.com>
>
>
> Subject: Re: [FRIAM] Oblivion resistant swarm
>
>
>
> This approach might be useful to understand such phase transitions.
> Imagine the agents have a pairwise influence network that attract or repel
> one another, and further any subset of agents can be biased left or right
> as a function of time (like from a political convention), or to uncertain
> states (superposition).
>
> https://science.sciencemag.org/content/361/6398/162
>
>
>
> *From: *Friam <friam-bounces at redfish.com> on behalf of Jochen Fromm <
> jofr at cas-group.net>
> *Reply-To: *The Friday Morning Applied Complexity Coffee Group <
> Friam at redfish.com>
> *Date: *Saturday, June 6, 2020 at 12:27 PM
> *To: *The Friday Morning Applied Complexity Coffee Group <
> Friam at redfish.com>
> *Subject: *[FRIAM] Oblivion resistant swarm
>
>
>
> I would like to add an agent-based model for the last chapter of my book.
> The idea is to use a classic swarm as a model for a religious or political
> movement (since the basic rules like global attraction and local repulsion
> are isomorphic, as I argue in earlier chapters).
>
>
>
> The new thing is an "oblivion" factor which causes agents to forget the
> classic Boids swarm rules step by step. In order to keep the swarm from
> dissolving the model reinforces the rules every T timesteps, which
> simulates a rally, convention or congregation for the movement. Therefore
> the name "Oblivion Resistant Swarm" (ORS model) :-)
>
>
>
> As T varies, I expect to find some kind of phase transition in simulations
> where the swarm forms or dissolves. If T is too large, the swarm forgets
> the rules and is unable to maintain the form. If T is very small we get the
> classic Boids model and the swarm is able to form. Does that make any
> sense? Two more questions:
>
>
>
> 1. Is two weeks a reasonable timespan for the time we need to learn new
> rules in general?
>
>
>
> 2. Do you know any existing ABMs which are similar?
>
>
>
> -J.
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
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> --
>
> Frank Wimberly
> 140 Calle Ojo Feliz
> Santa Fe, NM 87505
> 505 670-9918
>
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> Frank Wimberly
> 140 Calle Ojo Feliz
> Santa Fe, NM 87505
> 505 670-9918
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