I mean, it's not hard to imagine that scenario in a simulated training environment (though as others reported, this story is misreported, there was no sim, only

I mean, it's not hard to imagine that scenario in a simulated training environment (though as others reported, this story is misreported, there was no sim, only a thought experiment): You have a training environment that is symmetrical, you have enemy drone operators, that use an enemy communications network to give commands to units and to control their drones. You could maybe model the ability of each component to function/to contribute to the operation as a bayesian graph. You equally have the same infrastructure for your own drone. Now you try to get the drone to pick the right targets to impact the enemy operation maximally - if the operator could possibly minimize the drone's contribution, the operator not vetoing will maximize the success of each target engagement. You could see similar behavior with all kinds of "reach the goal in this simulated environment" training, where the model ended up using glitches or trivial solutions, if those weren't sufficiently penalized. If the story as reported were true, the fault would be in the simulation environment - the model for the drone just picks the path of least resistance.