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computer science Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, ...
and
mathematical logic Mathematical logic is the study of Logic#Formal logic, formal logic within mathematics. Major subareas include model theory, proof theory, set theory, and recursion theory (also known as computability theory). Research in mathematical logic com ...
, an infinite-tree automaton is a state machine that deals with infinite tree structures. It can be seen as an extension of top-down finite-tree automata to infinite trees or as an extension of infinite-word automata to infinite trees. A finite automaton which runs on an infinite tree was first used by Michael Rabin for proving decidability of S2S, the monadic second-order theory with two successors. It has been further observed that tree automata and logical theories are closely connected and it allows decision problems in logic to be reduced into decision problems for automata.


Definition

Infinite-tree automata work on \Sigma-labeled trees. There are many slightly different definitions; here is one. A (nondeterministic) infinite-tree automaton is a tuple A = (\Sigma, D, Q, q_0, \delta, F ) with the following components. * \Sigma is an alphabet. This alphabet is used to label nodes of an input tree. * D\subset \mathbb is a
finite set In mathematics, particularly set theory, a finite set is a set that has a finite number of elements. Informally, a finite set is a set which one could in principle count and finish counting. For example, is a finite set with five elements. Th ...
of allowed branching degrees in an input tree. For example, if D = \, an input tree has to be a
binary tree In computer science, a binary tree is a tree data structure in which each node has at most two children, referred to as the ''left child'' and the ''right child''. That is, it is a ''k''-ary tree with . A recursive definition using set theor ...
, or if D = \, then each node has either 1, 2, or 3 children. * Q is a finite set of states; q_0 is initial. * \delta: Q \times \Sigma \times D \rightarrow 2^ is a transition relation that maps an automaton state q \in Q, an input letter \sigma \in \Sigma , and a degree d \in D to a set of d-tuples of states. * F \subseteq Q^ is an accepting condition. An infinite-tree automaton is ''deterministic'' if for every q \in Q, \sigma \in \Sigma , and d \in D , the transition relation \delta( q, \sigma, d) has exactly one d-tuple.


Run

Intuitively, a run of a tree automaton on an input tree assigns automaton states to the tree nodes in a way that satisfies the automaton transition relation. A bit more formally, a ''run'' of a tree automaton A over a \Sigma-labeled tree (T,V) is a Q-labeled tree (T_r, r ) as follows. Suppose that the automaton reached a node t of an input tree and is currently in state q. Let the node t be labeled with \sigma \in \Sigma and d(t) be its branching degree. Then, the automaton proceeds by selecting a tuple (q_1,...,q_) from the set \delta( q, \sigma, d(t)) and cloning itself into d(t) copies. For each 0 < i \leq d(t), one copy of the automaton proceeds into node t.i and changes its state to q_i. This produces a run which is a Q-labeled tree. Formally, a run (T_r, r ) on the input tree satisfies the following two conditions. * r(\epsilon) = q_0. * For every t \in T_r with r(t) = q, there exists a (q_1,...,q_) \in \delta(q,V(t),d(t)) such that for every 0 < i \leq d(t) , we have t.i \in T_r and r(t.i) = q_i . If the automaton is nondeterministic, there may be several different runs on the same input tree; for deterministic automata, the run is unique.


Acceptance condition

In a run (T_r, r ), an infinite path is labeled by a sequence of states. This sequence of states form an infinite word over states. If all these infinite words belong to accepting condition F, then the run is ''accepting''. Interesting accepting conditions are Büchi, Rabin, Streett, Muller, and parity. If for an input \Sigma-labeled tree (T,V ), there exists an accepting run, then the input tree is ''accepted'' by the automaton. The set of all accepted \Sigma-labeled trees is called tree language \mathcal(A) which is ''recognized'' by the tree automaton A.


Expressive power of acceptance conditions

Nondeterministic Muller, Rabin, Streett, and parity tree automata recognize the same set of tree languages, and thus have the same expressive power. But nondeterministic Büchi tree automata are strictly weaker, i.e., there exists a tree language that can be recognized by a Rabin tree automaton but cannot be recognized by any Büchi tree automaton. (For example, there is no Büchi tree automaton that recognizes the set of \-labeled trees whose every path has only finitely many as, see e.g. ). Furthermore, deterministic tree automata (Muller, Rabin, Streett, parity, Büchi, looping) are strictly less expressive than their nondeterministic variants. For example, there is no deterministic tree automaton that recognizes the language of binary trees whose root has its left or right child marked with a. This is in sharp contrast to automata on infinite ''words'', where nondeterministic Büchi ω-automata have the same expressive power as the others. The languages of nondeterministic Muller/Rabin/Streett/parity tree automata are closed under union, intersection, projection, and complementation.


References


Literature

* In particular: Part II ''Automata on Infinite Trees'', pp. 165-185. * {{DEFAULTSORT:Infinite Tree Automaton Trees (data structures) Automata (computation)