  We propose a simplification of the Theory-of-Mind Network architecture, which
focuses on modeling complex, deterministic machines as a proxy for modeling
nondeterministic, conscious entities. We then validate this architecture in the
context of understanding engines, which, we argue, meet the required internal
and external complexity to yield meaningful abstractions.
