Does anyone have any thoughts on heuristics versus strong induction?
A heuristic technique (/hjʊəˈrɪstɪk/; Ancient Greek: εὑρίσκω, "find" or "discover" ), often called simply a heuristic, is any approach to problem solving, learning, or discovery that employs a practical method not guaranteed to be optimal or perfect, but sufficient for the immediate goals.
Inductive reasoning (as opposed to deductive reasoning or abductive reasoning) is a method of reasoning in which the premises are viewed as supplying strong evidence for the truth of the conclusion. While the conclusion of a deductive argument is certain, the truth of the conclusion of an inductive argument may be probable, based upon the evidence given.
They seem very much the same although I suppose that heuristic suggests an invented technique and induction suggest a way of reasoning, which may be heuristic but perhaps need not.
I like to read about babies learning:
A Gopnik [onlinelibrary.wiley.com] suggests that a prelinguistic baby approaches the world inherently using a Bayesian methodology to understand its causality.
For what it's worth, in 1974 at the Bronx High School of Science, after the intriductory computer course, my projects were all heuristics and machine learning. This was on an HP 3000 E, a refrigerator-sized machine with 16 K of RAM and which relied on paper tape for external storage. So my thought is that it has sentimental values for me. My big project was to have the computer cast and read I Ching hexagrams.
Well, strong induction is preferrable if you have the overhead to burn, but I think the reason we have heuristics is for sheer efficiency (and evolution is a notoriously parsimonious 'designer'. This may be why AI ends up surpassing us, because if we can get over the energy and speed requirements, they can use strong induction every time instead of relying upon heuristics.
I prefer to use deductive reasoning whenever possible. It's just more reliable.