Title :
RETE and chart parsing from bottom-up call-graph caching
Author_Institution :
Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
A new mechanism is presented for graph instantiation. It is used to investigate various bottom-up data-driven AI algorithms. The author views instances as fairly autonomous objects that inherit graph information (e.g. links or relations) from their classes. Instances themselves can be instantiated. For example, a parse tree symbol is an instance of a grammar class-graph symbol, which itself is a symbol of instance. The model focuses on underlying computational processes, and makes little use of program text. Instead of transforming programs, CGC (call graph caching) is used to instantiate processes. Experimental results show that RETE matching, efficient context-free parsing, and truth maintenance are different manifestations of the same underlying computational process
Keywords :
artificial intelligence; buffer storage; context-free grammars; pattern recognition; program compilers; RETE; bottom-up call-graph caching; bottom-up data-driven AI algorithms; chart parsing; computational processes; context-free parsing; fairly autonomous objects; grammar class-graph symbol; graph information; graph instantiation; parse tree symbol; truth maintenance; Artificial intelligence; Buildings; Computer science; Costs; Mirrors; Natural languages; Parallel processing; Topology; Tree data structures; Tree graphs;
Conference_Titel :
Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-8186-2300-4
DOI :
10.1109/TAI.1991.167027