EOM is NOT strictly speaking equivalent to the Two Generals Problem, or Distributed Consensus, in an unreliable network. In distributed consensus, at some given point in time, A has to know X, A has to know B knows X, A has to know B knows A knows X, ... It has to do with the fact that the message broker is in some sense the arbitrator of truth, so the consumer(s) don't need full consensus. In an unreliable network, you can have EOM. http://ilpubs.stanford.edu:8090/483/1/2000-7.pdf gives some examples of how that works.
HOWEVER, you can't have EOM when the consumers can fail. If a consumer fails there's no way, in general, to tell if the last message it was working on was completed.
There are a couple of edge cases where you can still have EOM. For instance, a system where you have a message broker A, and a bunch of consumers that read messages x from that queue, compute f(x), and insert f(x) onto message broker B, where f(x) may be computed multiple times for the same x (i.e. if f is a pure function or you don't care about the side effects). This system can implement EOM in the presence of an unreliable network and consumer failures (I think it can handle one or both of the message brokers failing too, not 100% sure) in the sense that x will never be in broker A at the same time as f(x) is in broker B, f(x) will never be in broker B more than once for the same x, and any y in B had some x that was in A such that y = f(x).