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- look at relationships between variables, a la ILP and MLNs and some recent work in differentiable programming - include a type-token distinction - don’t waste your time with bags of features; only consider architectures with structured representations - learn a common sense db
i have also made a strong specific claim about innateness, suggesting we should be focusing our efforts on finding mechanisms that can represent all of the following independently of experience:pic.twitter.com/x3N32jqcv6
All animals (bugs/birds/us) have many innate behaviors, eg nest building, mating, hunting, etc Your list seems very human-specific (eg "type-token") So for each animal you need to handcraft a new set of innate mechs? Or is there a common framework? Eg "genomic bottleneck"?
type-token is not human-specific; i review animal evidence up to 2000 in The Algebraic Mind.
I see the list having two problems (1) It doesn't identify intermediate animal cognition that may be necessary stepping stones and (2) it does not specify the mechanisms of how cognition develops these capabilities. Endpoints but no prescriptions on how to get there.
i review animal evidence in algebraic mind; agree it is prescription, do give some suggestions there.
IMHO, the above specs are far more than just "search a different part of a model space". Problem with AI world - over selling existing models and theories of AI while completely ignoring a fairly human level specs for AI. Agreeing on specs is 1st step to finding testable solution
Onlooker: "How do you propose to move the field forward?"
Marcus: "I want a machine with the following abilities."
Onlooker: "How do you propose to program those abilities?"
Marcus: "Once we incorporate those abilities, the machine will be ready."
Onlooker: "OK, Boomer." 
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