Yeah, I wish we had some cleaner terminology for that. Finetuning the “simulation engine” towards a particular task at hand (i.e. to find the best trade-off between breadth and depth search in strategy games, or even know how much “thinking time” or “error allowance” to allocate to a move), given limited cognitive resources, is something that I would associate with level 3 capability. It certainly seems like learning could go into the direction of making the model of the game more useful by either improving the extent to which this model predicts/ouputs good moves or by improving the allocation of cognitive resources to the sub-tasks involved. Presumably, an intelligent system should be capable of testing which improvement vectors seem most fruitful (and the frequency with which to update this analysis), but I find myself a bit confused about whether that should count as level 3 or as level 4, since the system is reasoning about allocating resources across relevant learning processes.
Yeah, I wish we had some cleaner terminology for that.
Finetuning the “simulation engine” towards a particular task at hand (i.e. to find the best trade-off between breadth and depth search in strategy games, or even know how much “thinking time” or “error allowance” to allocate to a move), given limited cognitive resources, is something that I would associate with level 3 capability.
It certainly seems like learning could go into the direction of making the model of the game more useful by either improving the extent to which this model predicts/ouputs good moves or by improving the allocation of cognitive resources to the sub-tasks involved. Presumably, an intelligent system should be capable of testing which improvement vectors seem most fruitful (and the frequency with which to update this analysis), but I find myself a bit confused about whether that should count as level 3 or as level 4, since the system is reasoning about allocating resources across relevant learning processes.