Carl,Nice Schwarzenegger video :-) I am trying to model a movement in general
where the agents are forgetful, for instance a political movement or an
ideological group. If all of us forget to attend the FRIAM group on Friday
mornings or the members of "Fridays for Future" forget what they are protesting
for then these groups would stop to exist.Therefore I have tried to construct a
swarm model to see if a group is able to form when the members tend to forget
the rules but are reminded of them periodically. As the time intervals between
these reminders vary, how does the group react, how fast does it disintegrate
if the agents forget the rules? How often do they have to be reminded of the
rules to form a stable group?The simulation results indicate that the time
between regular reminders should ideally be less or equal than the half life of
the memory loss for the agents. Assuming that the half life of newly learned
rules is about one week, a group needs to meet each week to ensure new rules
are remembered correctly. So one reason why we are supposed to sit every week
on a church pew is that we have to be reminded of the rules like "love your
neighbor as yourself" or "you shouldn't covet your neighbor's wife". This might
seem to be obvious, but for forgetful participants it is indeed necessary to
meet regularly in order to learn the rules.-Jochen
-------- Original message --------From: Steve Smith <[email protected]> Date:
6/8/20 22:52 (GMT+01:00) To: [email protected] Subject: Re: [FRIAM] Oblivion
resistant swarm
Jochen -
I'm glad I didn't jump in earlier and let some of this play out.
I hope I'm not still jumping in too early ('you move too
soon') here... but as with Tom's question, I'm not sure
what you are trying to model with "forgetting"? Is this adding
thermal noise to the rules on principle (annealing) or does it
model something like a loss/fading of allegiance to an affinity
group over time?
I did a half-ass search for the pre-thread when you talked about
your book-in-progress to see what I might have missed there.
More background would be interesting to me.
- Steve
Stephen,
here are some first simulation results. I took a
classic Boids model and made the Boids forgetful. They lose the
memory of the rules, and I have simply used the classic "curve
of forgetting". The "curve of forgetting" describes the
exponential rate at which something is forgotten after it is
initially learned. Using Python and Matplotlib it looks like
this and describes the memory loss of an agent
https://en.wikipedia.org/wiki/Forgetting_curve
To counteract the memory loss the agents are
taught the rules again at regular "teaching" intervals.
After a teaching event the agents start to forget again. If
this teaching interval exceeds the half life time of the
curve of forgetting, the swarm starts to disintegrate as
expected.
https://en.wikipedia.org/wiki/Half-life
-Jochen
-------- Original message --------
From: Stephen Guerin <[email protected]>
Date: 6/6/20 23:24 (GMT+01:00)
To: The Friday Morning Applied Complexity Coffee Group
<[email protected]>
Subject: Re: [FRIAM] Oblivion resistant swarm
Jochen,
Here's a video recording I made this afternoon for
you using Josh Thorp's Processing flocking model for a student
lesson for 6-12th graders in the NM Supercomputing Challenge
that shows this kind of manipulation of the control parameter
to move the flocking through its phase transition
https://bit.ly/FlockingPhaseTransition
(turn on the audio for narration)
To make an interactive example to run on line, you could use
Owen's flocking model in Agentscript using a 3D View:
http://backspaces.github.io/as-app3d/models/?flock
or add a UI to the 2D version:
https://backspaces.github.io/agentscript/models2/flock.html
Either could be modified to add an interface to manipulate
the micro rules to move the system through the phase
transition of "flocking / no flocking" like I was doing in
the movie. I would operationalize that with an order
parameter of an entropy on the collective heading or a kind
of "linear momentum".
Also, definitely check out the Netlogo Web option as there's
some very nice "alternative visualization" approaches:
https://www.netlogoweb.org/launch#https://www.netlogoweb.org/assets/modelslib/Alternative%20Visualizations/Flocking%20-%20Alternative%20Visualizations.nlogo
In the top search bar: type in "flock" to see
alternatives.
Or download Netlogo and search in the netlogo library.
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On Sat, Jun 6, 2020 at 1:27 PM
Jochen Fromm <[email protected]> wrote:
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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