Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
In this paper, we propose a new framework for the computational learning of formal grammars with positive data. In this model, both syntactic and semantic information are taken int...
Abstract. We introduce dynamic communicating automata (DCA), an extension of communicating finite-state machines that allows for dynamic creation of processes. Their behavior can ...
Attribute grammars may be seen as a (rather specialised) lazy or demand-driven programming language. The "programs" in this language take text or parse trees as input an...
This paper studies the computational complexity of disambiguation under probabilistic tree-grammars as in (Bod, 1992; Schabes and Waters, 1993). It presents a proof that the follo...