|
A filtered-popping recursive transition network (FPRTN),〔Javier M. Sastre, ("Efficient parsing using filtered-popping recursive transition networks" ), ''Lecture Notes in Artificial Intelligence'', 5642:241-244, 2009〕 or simply filtered-popping network (FPN), is a recursive transition network (RTN)〔 William A. Woods, ("Transition network grammars for natural language analysis" ), ''Communications of the ACM'', ''ACM Press'', 13:10:591-606, 1970〕 extended with a map of states to keys where returning from a subroutine jump requires the acceptor and return states to be mapped to the same key. RTNs are finite-state machines that can be seen as finite-state automata extended with a stack of return states; as well as consuming transitions and -transitions, RTNs may define call transitions. These transitions perform a subroutine jump by pushing the transition's target state onto the stack and bringing the machine to the called state. Each time an acceptor state is reached, the return state at the top of the stack is popped out, provided that the stack is not empty, and the machine is brought to this state. Throughout this article we refer to filtered-popping recursive transition networks as ''FPNs'', though this acronym is ambiguous (e.g.: fuzzy Petri nets). ''Filtered-popping networks'' and ''FPRTNs'' are unambiguous alternatives. ==Formal Definition== A FPN is a structure where * is a finite set of states, * is a finite set of keys, * is a finite input alphabet, * is a partial transition function, being the empty symbol, * is a map of states to keys, * is the set of initial states, and * is the set of acceptance states. 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Filtered-popping recursive transition network」の詳細全文を読む スポンサード リンク
|