Potentially, the advantages of marker-passing over local connectionist techniques for associa tive inference are (1) the ability to differen tiate variable bindings, and (2) reduction in the search space and/or number of processing elements. However, the latter advantage has mostly been realized at the expense of accu racy and predictability. In this paper we con sider a class of associative inference to which marker passing is often applied, variously called abductive inference, schema selection, or pat tern completion. Analysis of marker seman tics in a standard semantic net representation leads to a proposal for more strictly regulated marker propagation. An implementation strat egy employing an augmented relaxation net work is outlined.