Good question — leaving out comparison with a traditional state machine wasn't intentional so I'm glad you asked.
A state machine will typically fully describe all the state at any given node in it. i.e. there's no additional state or context not represented by the state machine itself.
In our case, we have (1) the directed graph and (2) the session state. These two are related but don't have a direct correlation. The session state accrues new values as the graph is walked. As an example, theoretically the user could walk through a graph that has a cycle and get back to an earlier node but the session state would be different. In that case the same node would be "current" but there would be a different session state the second time it was visited.
A state machine will typically fully describe all the state at any given node in it. i.e. there's no additional state or context not represented by the state machine itself.
In our case, we have (1) the directed graph and (2) the session state. These two are related but don't have a direct correlation. The session state accrues new values as the graph is walked. As an example, theoretically the user could walk through a graph that has a cycle and get back to an earlier node but the session state would be different. In that case the same node would be "current" but there would be a different session state the second time it was visited.