Eliezer’s comment describes the importance of Jumping Out Of The System, which I attribute to the “cross-domain” aspect of intelligence, but I don’t see this defined anywhere in the formula given for intelligence, which so far only covers “efficient” and “optimizer”.

First, a quick-and-dirty description of the process: Find an optimization process in domain A (whether or not it help attain goals). Determine one or many mapping functions between domains A and B. Use a mapping to apply the optimization process to achieve a goal in domain B.

I think the heart of crossing domains is in the middle step—the construction of a mapping between domains. Plenty of these mappings will be incomplete, mere projections that lose countless dimensions, but they still occasionally allow for useful portings of optimization processes. This is the same skill as abstraction or generalization: turning data into simplified patterns, turning apples and oranges into numbers all the same. The measure of this power could then be the maximum distance from domain A to domain B that the agent can draw mappings across. Or maybe the maximum possible complexity of a mapping function (or is that the same thing)? Or the number of possible mappings between A and B? Or speed; it just would not do to run through every possible combination of projections between two domains. So here, then, is itself a domain that can be optimized in. Is the measure of being cross-domain just a measure of how efficiently one can optimize in the domain of “mapping between domains”?

Eliezer’s comment describes the importance of Jumping Out Of The System, which I attribute to the “cross-domain” aspect of intelligence, but I don’t see this defined anywhere in the

formulagiven for intelligence, which so far only covers “efficient” and “optimizer”.First, a quick-and-dirty description of the process: Find an optimization process in domain A (whether or not it help attain goals). Determine one or many mapping functions between domains A and B. Use a mapping to apply the optimization process to achieve a goal in domain B.

I think the heart of crossing domains is in the middle step—the construction of a mapping between domains. Plenty of these mappings will be incomplete, mere projections that lose countless dimensions, but they still occasionally allow for useful portings of optimization processes. This is the same skill as abstraction or generalization: turning data into simplified patterns, turning apples and oranges into numbers all the same. The measure of this power could then be the maximum distance from domain A to domain B that the agent can draw mappings across. Or maybe the maximum possible complexity of a mapping function (or is that the same thing)? Or the number of possible mappings between A and B? Or speed; it just would not do to run through every possible combination of projections between two domains. So here, then, is itself a domain that can be optimized in. Is the measure of being cross-domain just a measure of how efficiently one can optimize in the domain of “mapping between domains”?