2012 Conference on Technologies and Applications of Artificial Intelligence (TAAI) (2012)
Nov. 16, 2012 to Nov. 18, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TAAI.2012.44
A method to represent first-order predicate logic (Horn clause logic) by a data-flow network is presented. Like a data-flow computer for a von Neumann program, the proposed network explicitly represents the logical structure of a declarative program by unlabeled edges and operation nodes. In the deduction, the network first propagates symbolic tokens to create an expanded AND/OR network by the backward deduction, and then executes unification by a newly developed method to solve simultaneous equations buried in the network. The paper argues the soundness and completeness of the network in a conventional way, then explains how a kind of ambiguous solution is obtained by the new developed method. To examine the method's convergence property, numerical experiments are also conducted with some simple data-flow networks.
convergence of numerical methods, data flow computing, data flow graphs, Horn clauses, inference mechanisms, symbol manipulation
H. Suzuki, M. Yoshida and H. Sawai, "A Data-Flow Network That Represents First-Order Logic for Inference," 2012 Conference on Technologies and Applications of Artificial Intelligence(TAAI), Tainan, Taiwan Taiwan, 2013, pp. 211-218.