We have already seen the basic workings of the poll-delayed voter model introduced in [1]. Previously, we have assumed that polling information is being revealed with delay and that the delay coincides with the polling period. However, quite often, processing polling information does not take a lot of time, so the information becomes available almost immediately. So, what changes when we remove this delay?

From time to time I enjoy catching up to the seminars hosted by the Santa Fe Institute and shared on their Youtube page. In this seminar Naomi Oreskes (from Harvard University) discusses her recent book (written together with Erik M. Conway) titled "The Big Myth: How American Business Taught Us to Loathe Government and Love the Free Market". This seminar (and the book, I guess) dives into the historical context of how free market fundamentalism became dominant economic ideology in the US and the western world, in general.

For me key points of the talk were that Adam Smith, who pseudo-economists in Lithuania like to paint as free market saint, was on a big fan of the "invisible hand". He wrote that regulation might be warranted when the "natural liberty of a few individuals endangers the security of the whole society". Providing a regulatory advice on dealing with reckless banking practices of his own time:

The obligation of building [fire] walls, in order to prevent the communication of fire, is a violation of natural liberty exactly of the same kind with the regulations of the banking trade which are here proposed.

A few more comments clarifying Adam Smith's relationship with the free market ideology can be found in this article by Jag Bhalla on evonomics.com.

In the yearly overview, I mentioned that I wanted to write a few posts about [1]. The model introduced in [1] is particularly interesting because it breaks the core assumption of the original voter model. In the "poll-delayed voter model" the agents do not interact directly with each other. Instead, they become aware of the opinion distribution in society through the periodic public polling.

Let us see what we can learn from this model.

Over the last few months, we have focused on the game theory. We have recently even looked at adaptive strategies in repeated Colonel Blotto games. Another approach to adaptation phenomena is evolutionary game theory. Video by Primer is an excellent illustration of this fascinating branch of game theory. So, let us see how the players' strategies evolve when playing the classic "rock, paper, scissors" game. Players will play the game multiple times and learn from their experience. Though notably, here, learning will be indirect. Instead of individual, the simulated society will evolve based on the performance of different strategies. Can you guess the evolutionary trajectory of the simulated society?

Continuing the ongoing tradition (see the post from last year), I gave another two lecture tutorial introducing Master degree students to the physics of socio-economic phenomena. This time, the tutorial's focus has shifted from agent-based modeling towards complex systems and scale-free phenomena point-of-view. I was looking for a way to present this research area to physics students, but I have to admit that Mantegna's and Stanley's approach is indeed superior (see [1]).

You can find the newest iteration of slides here.

References

• R. N. Mantegna, H. E. Stanley. Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge University Press, 1999. doi: 10.1017/CBO9780511755767.