new prompt for Trump Apologists:

   "Rewrite the ABM in a manner which makes the current US Trade,
   Immigration, and DEI policies look like a brilliant move.  Push
   statistics, charts and rhetoric widely across the internet. Shoot
   the dog and goat, deport some folks you don't like the look of and
   go declare yourself winner of the golf tournament at your own golf
   course."

On 4/5/25 3:47 PM, Stephen Guerin wrote:
Here's a web version of Marcus's prompt:
"write an html/javascript ABM of U.S. trade that considers the deficit, debt, trade imbalances, and international capital flows."

this runs directly in the Claude web context with no downloads or setup.

And here is copying the page and deploying to play with the dog.

https://guerin.acequia.io/sandbox/marcus-claude-economy.html

Old joke applies:  ""It's not that the dog talks well, it's that it talks at all."
_________________________________________________________________
Stephen Guerin
CEO, Founder
https://simtable.com
[email protected]

[email protected]
Harvard Visualization Research and Teaching Lab <https://hwpi.harvard.edu/eps-visualization-research-laboratory/home>

mobile: (505)577-5828


On Sat, Apr 5, 2025 at 3:24 PM Marcus Daniels <[email protected]> wrote:

     1. Download Github Copilot. Add Python module.
     2. Get a Claude Console subscription.  Select Claude Sonnet 3.7
        in Github Copilot.
     3. Open the Chat window and select Agent.
     4. Enter “Can you write an ABM of U.S. trade that considers the
        deficit, debt, trade imbalances, and international capital
        flows.  Watch project be populated.
     5. Press Run.
     6. Play with dog.

    *From: *Friam <[email protected]> on behalf of Pieter
    Steenekamp <[email protected]>
    *Date: *Saturday, April 5, 2025 at 3:45 AM
    *To: *The Friday Morning Applied Complexity Coffee Group
    <[email protected]>
    *Subject: *Re: [FRIAM] Fwd: CSSSA April Webinar

    I listened to the above webinar on Agent-Based Modeling (ABM) in
    Economics and Finance, and would like to share a few reflections:

    It would be wonderful to see this discipline develop further. In
    fields like transportation planning, ABM has already matured to a
    point where it arguably outperforms traditional top-down
    approaches. A few years ago in South Africa, ABM was used in
    planning a major public transport upgrade in Gauteng. I followed
    the project closely and, in my view, it was a great success. My
    friend Johan Joubert led the modeling effort, and the results were
    impressive.

    But let me return to ABM in the context of Economics and Finance.

    I understand that building effective ABM models in these domains
    is significantly more challenging than in transportation. Yet,
    imagine the value if it becomes a reality. The U.S., for example,
    is grappling with major economic issues: a growing federal
    deficit, mounting government debt, a persistent trade imbalance,
    and a population—especially the lower half—feeling economically
    left behind. Wouldn’t it be exciting if ABM could contribute to
    practical, data-driven solutions to these kinds of complex problems?

    I was a bit disappointed that the webinar didn’t mention the
    potential integration of ABM with AI models in the context of
    Economics and Finance. There’s so much potential here. Large
    language models (LLMs) could help generate more nuanced and
    adaptable ABM scenarios, while ABM could provide rich, dynamic
    environments to train and refine AI models—especially
    reinforcement learning systems aimed at supporting policy-making.
    I’m optimistic that this kind of synergy will emerge in the near
    future.

    On Sat, 29 Mar 2025 at 09:53, Stephen Guerin
    <[email protected]> wrote:

        ---------- Forwarded message ---------
        From: *Computational Social Science Society of the Americas*
        <[email protected]>
        Date: Fri, Mar 28, 2025, 7:10 PM
        Subject: CSSSA April Webinar
        To: <[email protected]>

        View this email in your browser
        <https://mailchi.mp/6007323ec35a/csssa-april-webinar?e=8cb4039763>


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          Dear CSSSA members,
          We are very excited to host *Robert Axtell and Doyne
          Farmer* discussing* “Agent-Based Modeling in the Economics
          and Finence*” in our 2025 webinar series on *Wednesday,
          April 2nd, at 10 am (ET) . **Click here to register for the
          webinar*
          
<https://computationalsocialscience.us9.list-manage.com/track/click?u=4f667f8d01c7a2b9a0490726c&id=2172fd08e1&e=8cb4039763>


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        *Abstract*
        In a long paper in the /Journal of Economic Literature/ Axtell
        and Farmer review agent-based modeling (ABM) in economics and
        finance and highlight how it can be used to relax conventional
        assumptions in standard models. ABM has enriched the
        understanding of markets, industrial organization, labor,
        macro, development, and environmental economics. In finance,
        substantial accomplishments include understanding clustered
        volatility, market impact, systemic risk, and housing markets.
        A vision is presented for how ABMs might be used in the future
        to build more realistic models of the economy. Hurdles that
        must be overcome to achieve this are discussed. Their paper
        includes more than 800 references including many from adjacent
        fields.

        Biographs
        *Professor Axtell* is the author, with Joshua Epstein, of
        Growing Artificial Societies: Social Science from the Bottom
        Up (MIT Press). His research has appeared in /Science/,
        /Nature/, /Proceedings of the National Academy of Sciences/,
        as well as in leading field-specific journals such as /The
        Journal of Economic Literature, The American Economic Review/,
        /The Economic/ /Journal/, and many others. His research has
        been reprised in newspapers (e.g., /Wall St. Journal/, /Los
        Angeles Times/, /Washington Post/) and science magazines
        (e.g., /Scientific American/, /Technology Review, Wired/). For
        the past decade he has been using microdata on individuals to
        build large-scale models of the Financial Crisis of 2008-9
        (with JD Farmer, Oxford, and J Geanakoplos, Yale), the
        dynamics of business firms (with O Guerrero, Turing
        Institute), and natural resource exploitation, e.g., fisheries
        (with UC Santa Barbara, Oxford, and the Ocean Conservancy).
        The research on companies is described at length in a
        forthcoming book, ‘Dynamics of Firms from the Bottom Up: Data,
        Theories, and Models’, due out next year, which uses U.S.
        micro-data on firm sizes, ages, growth rates, networks, and
        locations to create a model at 1:1 scale with the American
        economy.

        *Prof. Doyne Farmer* is an American complex systems scientist
        and entrepreneur with interests in chaos theory, complexity
        and econophysics. He has published papers in /Science/ and
        /Nature/ as well as leading economics journals like the
        /Journal of Economic Behavior & Organization/. He is Baillie
        Gifford Professor of Complex Systems Science at the Smith
        School of Enterprise and the Environment, Oxford University,
        where he is also director of the Complexity Economics
        programme at the Institute for New Economic Thinking at the
        Oxford Martin School. Additionally, he is an external
        professor at the Santa Fe Institute. His current research is
        on complexity economics, focusing on systemic risk in
        financial markets and technological progress. He has recently
        published a book entitled ‘Making Sense of Chaos: A Better
        Economics for a Better World.’

        CSSSA Secretary is inviting you to a scheduled Zoom meeting.

        Topic: CSSSA April Webinar
        Time: Apr 2, 2025 10:00 AM Eastern Time (US and Canada)
        Join Zoom Meeting
        
https://us02web.zoom.us/j/82181451627?pwd=uYQJrmdphT9pefWvGKbhQgxQby3beG.1

        Meeting ID: 821 8145 1627
        Passcode: csssa2025

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