An augmented transition network or ATN is a type of graph theoretic structure used in the operational definition of formal languages, used especially in parsing relatively complex natural languages, and having wide application in artificial intelligence.
ATN are modified transition networks and an extension of RTNs[citation needed].
ATNs build on the idea of using finite-state machines (Markov model) to parse sentences.
Woods in "Transition Network Grammars for Natural Language Analysis" claims that by adding a recursive mechanism to a finite state model, parsing can be achieved much more efficiently.
Such encapsulation not only simplifies the grammar, but has the added bonus of efficiency of operation.