Like everyone in his field he has probably encountered Herbert Simon before. But as far as "Intelligence is Search" goes, Herb thought that "search" is a subset of problem solving, next to "reasoning" and "constraints". In the end they could all be considered as being unified under "traversal of state-space" for a given problem. Creativity or imagination can be thought of as generating useful representations and possibilities for states within that space.
Anything of his that you find particularly singular or encapsulating these ideas?
Also, it was just Simon's centenary.
Good brief interview with Simon: https://www.youtube.com/watch?v=ErnWbP_Wztk
After looking at Herbert's wiki, I feel like I've been creeping around his ideas for much of my life without realizing he was the progenitor, to the point where a few comments ago I used a word he invented. Krakauer's ideas too really resonate, these guys are really onto something.
Tentatively dipping a toe into complex adaptive systems and the Sante Fe institute also keeps coming up time and time again, they seem to have captured everybody thinking about this in depth.
Does anybody have good leads on Krakauer and Simon's ideas? e.g. books for a dive into?
Hoping for a Adaptive Complexity for Dummies!
I had this exact feeling as well. Herb thought at the exact same level of abstraction that I like to think in, broadly construed as "models", not too rigorous to be mathematics, but not too loose to be raw observational psychology. Just right. Marvin Minksy is precisely the same but for AI systems rather than humans.
Krakauer's website is where I would read Krakauer: http://tuvalu.santafe.edu/~krakauer/Site/Publications.html
Scott E Page and his "Model Thinking" course on Coursera is in the same vein as these two. He's a complexity theorist that deals with proper representation of social networks and distributed decision-making. His books "The Difference" and "Complex Adaptive Systems" are academic but extremely readable, and don't harken after the same Cellular Automata and Chaos examples without at least operationalizing them into some application first.
I'm not sure regarding Krakauer, though I'm pretty positive he's published. SFI are _quite_ good about posting papers and such online, something I discovered after scanning in two books on a 30s/page scanner.... (I've since found faster scanners to use...) Though the published papers don't have the full formulae and typesetting of the published work.
> Though the published papers don't have the full formulae and typesetting of the published work.
Maybe email the author.
Krakauer: Intelligence is Search. It's the ability to find a least-energy path or solution through an arbitrary n-dimensional space.
Knowledge is having a solid backing of (valid) data and models.
Ignorance is not having that data and model store. It's a curable state, though being primed with bad data and models is very damaging to effective search.
Krakauer gave a really good interview at Nautilus a year or so back on this, it's very highly recommended.
http://m.nautil.us/issue/23/dominoes/ingenious-david-krakaue...
Farmer, quoting Muth, looks at a model of engineering in which engineers generate solutions at random but are very good at identifying the better solution. I'm thinking that there are emperical reasons to suspect that this may not be far from the truth, and methods such as A/B testing seem to explicitly embody the identification element of this.
You'll find this covered in many of Farmer's recent talks (past few years), Martin School at Oxford and Nanjing University in particular, at YouTube.
https://m.youtube.com/watch?v=u6x10eBpAPo