 We demonstrate that, through a reinforcement learning policy (or even simple heuristics), one can produce deceptively perturbed KGs  which maintain the downstream performance of the original KG while significantly deviating from the original  semantics and structure.
<clarity>  We demonstrate that, through a reinforcement learning policy (or even simple heuristics), one can produce deceptively perturbed KGs  which maintain the downstream performance of the original KG while significantly deviating from the original  semantics and structure.
 We show that, through a reinforcement learning policy (or even simple heuristics), one can produce deceptively perturbed KGs which maintain the downstream performance of the original KG while significantly deviating from the original semantics and structure.