"... Ecorithms are nature's (evolution's) algorithms . This is the idea of computational theorist Leslie Valiant (4), but none have been discovered yet. ...
(4) Valiant L, "Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World" ..." (typo in original at time of this communication)
According to Leslie Valiant, "... the goal of learning is to perform well in a world that isn't precisely modeled ahead of time. A learning algorithm takes observations of the world, and given that information, it decides what to do and is evaluated on its decision. A point made in my book is that all the knowledge an individual has must have been acquired either through learning or through the evolutionary process. And if this is so, then individual learning and evolutionary processes should have a unified theory to explain them."
https://www.quantamagazine.org/20160128-ecorithm-computers-and-life/ "Searching for the Algorithms Underlying Life" by John Pavlus (interviewing Leslie Valiant), 28 January 2016
It seems to me that there are serious problems with the scientific definitions of "goal", "learning", and what it means to "perform well". Does an oak tree learn? Is there learning in the system consisting of acorns and oak trees within a Northern hardwood forest? Does Valiant's concept of "ecorithm" involve deep problems in the foundations of quantum theory? How relevant is what Francis Crick called "molecular psychology" to the theory of machine learning?