Saturday, November 14, 2015

Report of Conference on Social Science Simulation

On the recent weekend of October 29 – November 1, I attended this year’s conference of The Computational Social Science Society of the Americas, at Santa Fe, New Mexico. This Society emphasizes computerized agent-based modeling. So their work bears some relation to my project in this blog. My project, to give a clue to newcomers, is exposition of a new model of our human experience, the Resource-Patterns Model of Life (RPM). Below I will comment upon two of the papers presented at Santa Fe. The second of those papers led me to read a few papers by Robert Axtell. I will end my comments here with what I found in Axtell’s papers. Overall I found affirmation in the conference. Affirmation, that is, of the approach to modeling I use in this RPM project.

Mirta Galesic presented her paper with Daniel Barkoczi, “Social learning strategies, network structure and the exploration-exploitation tradeoff”. The “social learning” subject of this paper catches my attention because social learning could describe the main question of interest that arises in RPM. Evidently this paper is only a small part of a body of literature on social learning now available. This literature has a context which bears some relation to RPM, so it will need to be studied as research is undertaken on social learning within RPM.

Digression: Before proceeding with the remainder of this post let me tell that I struggle to understand what I am doing on this blog. In a sense my drive is clear: I am promoting RPM which gives a better understanding of some important facts of life. But I have paused over questions such as: What is a model? Does conjecture have a place in science? I want my methods of both science and communication to withstand scrutiny. So I am looking for guidance, looking for what I may learn from the experience of others — especially those who have labored to communicate new agent-based views of science.

With that said let me say that in RPM the agents and their world remain, at this stage, mostly a thought experiment. I have started to computerize the agents as I reported earlier, but that effort did not promise enough rewards at this stage to justify the time it would require. So I am presenting a thought-experiment agent-based model of economic and psychological life.

Matthew Koehler presented a paper “Exploring Organizational Learning and Structuring”. But for me the most interesting part of Matt’s presentation was a long digression with which he started. In this digression he talked about the degree of specificity of agent-based models, praising what he had learned from Robert Axtell’s papers (see below). Matt showed a table (unfortunately not in the available paper) in which one axis represented the degree of specificity. Thought experiments were shown at the low-specificity end of that axis. I was heartened to see this because it seems to endorse the usefulness, within a broad view of science, of thought experiments at the early stage of development of scientific theories.

Matt also offered a suggestion for how to make a paper about a computerized agent-based model more meaningful to a reader. This was to lay out natural-language sentences, the sentences describing the agents and their world, in the first column of a table. Then in the second column give a reference to the computer code, that is to the line numbers of computer code in an appendix with the paper. This linking of natural language to computer language would empower a careful reader to understand exactly what is meant by the unavoidably fuzzy meanings of natural-language sentences. It may be impossible for some readers to gain a comfortable feeling of comprehension without such specifics. That may be helpful for me with exposition RPM. In some cases I have told more detail than I had believed necessary at first. But still I do not know how much detail to spill.

Robert Axtell, cited by Matt Koehler, has written in two papers (see references below) about a helpful way to categorize agent-based models. He suggests models be evaluated based upon their correlation at two levels with the empirical world. The two levels are the micro level of the agents and the macro level of system-wide developments. In each of these levels correlation with the empirical world is ranked, ranked to be either qualitative or quantitative, with quantitative judged to be better. This categorization ranks a model with a number from 0 to 3, with 3 being awarded to models which correlate with the empirical world at both micro and macro levels.

To equate Axtell’s terms “micro” and “macro” with what we use in RPM, recall that RPM allows for consideration of life in four or more levels. Almost all of our attention in RPM will focus upon the psychological implications of how living things on one level may advance to the next higher level. So Axtell’s term "micro" might refer to any level n in RPM, and then "macro" refer to level n+1. Also, micro might refer to the critters and macro to the organizations of critters which form in response to resource patterns.

RPM would be ranked at the lowest level in Axtell’s categorization scheme, because it is not close to empirical quantification at either micro or macro level. But that is alright, because RPM is still in the early fuzzy-language stage of paradigm development.


R. Axtell (2005). “Three Distinct Kinds of Empirically-Relevant Agent-Based Models”. Brookings Institute, 30 September 2005.

R. L. Axtell, and J. M. Epstein (1994). "Agent-Based Models: Understanding Our Creations". Bulletin of the Santa Fe Institute, Winter 1994, pp 28–32.

Daniel Barkoczi, and Mirta Galesic (2015). “Social learning strategies, network structure and
the exploration-exploitation tradeoff”. CSSSA 2015 link.

Matthew Koehler, Luciano Oviedo, and Michael Taylor (2015). “Exploring Organizational Learning and Structuring”. CSSSA 2015 link.

Saturday, November 7, 2015

Steve Schapiro, Scenes of Art

Last weekend I attended an agent-based conference in Santa Fe, New Mexico. I expect to share a few notes about that conference in my next post. But let’s start with some serendipity. On my trip home I met Steve Schapiro, a photographer from Chicago. Chance tossed us together on two legs of the journey: the shuttle to Albuquerque then the flight to Chicago.

Steve showed me this. When you are eating a meal either alone or in company — stop — sometime during the course of the meal. Look at the scene before you on the table. The arrangement of food and implements will be a scene of art. It will be perfect. You cannot improve it. If you try to improve it by moving things around you will only break it. You will make it worse.

First Steve told me about this, then later he proved it. After I had mostly finished my airline snacks and cup of coffee, he stopped me to look at the tray-table in front of me. It was indeed a satisfying scene of art.

What a delight!

Of course I can’t leave this alone. I need to explain this phenomenon. Here goes my attempt.

The scene invites you to participate. A person looking into that scene may know exactly where he or she would start. When I look at that scene I feel an impulse in my arm to start an action.

One reason for this feeling is, I suppose, that almost everything in the scene was made for use with human hands. The table, utensils, napkin, and servings of food were all made for human touch.

Let us compare the scene of a partially completed meal with three alternative scenes:
meal just set
If we look at the table with everything set in place but the meal not yet commenced, we human observers might know how we would start but we are not sure we have permission. Is this place setting mine or someone else’s? Has the time to dig in been signaled? It would be improper if we started without these permissions. The scene does not quite invite my participation.
craftsman’s workbench
We might look at a midday scene on a craftsman’s workbench and, as in the scene of a meal in progress, see objects which were made for use with human hands. But if I am not familiar with that particular craft I do not have any sense of what I would do next. The scene does not invite my participation.
extra-human landscape
A natural landscape with no evidence of human existence may appear beautiful to my human eye but this sense of beauty differs from the art I sense in a partially completed meal. I do not know how or if I would start to do anything in this scene. It does not invite my participation.

Why, you might ask, am I writing about scenes of art in this blog which has the purpose of promulgating the Resource-Patterns Model of Life? Psychology. The main interest which I find in RPM is its implication that we living things are probably biased to search for resource patterns. Such searches might be expressed as instincts or impulses. And this could possibly include our sense of art.

I could grope forward here to propose more specifically-worded ways that a sense of art may help LTs find RPs. But I prefer to encourage the reader to think in that way.

Addition: March 23, 2016
David Sloan Wilson seems to deal with a similar question. See for example Chapter 16 in Evolution for Everyone: How Darwin's Theory Can Change the Way We Think About Our Lives, (2007). Wilson looks into this question from a different model, a different perspective, although there are strong parallels.