The rate of learning had a big impact on how close you were to the classical model. If our little investors were slow at learning if the system didn't learn fast enough then nothing much would happen. But if we dialed up and we could do this easily on the computer the rate at which agents might explore new ideas and invest in those new ideas and learn from those new ideas we dialed that up with one little dial suddenly all this behavior would emerge, Brian says. "For me I think I got one of the many or several thrills of my life," he adds.
In our last episode, we heard from W. Brian Arthur, who shared his journey in economics as he studied increasing returns. Now, Brian's going to take us to 1987, to a small meeting in the Rockies in Santa Fe. At this time, he was struggling to gain recognition for his work within the economics community, but it was when Brian went to what would become the Santa Fe Institute that things really kicked off.
In this episode, you're going to hear again from W. Brain Arthur, External Professor at the Santa Fe Institute, and Researcher at Palo Alto Research Center, as he remembers the early days of the Santa Fe Institute. From the early meetings of economists, physicists, and a biologist that started it all, to an early model Brian built of a stock market that was unique to any models before it — because this model included booms and busts.
Connect:
This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.