Parallelism in Artificial Intelligence Problem Solving: A Case Study of Hearsay II

Abstract

The Hearsay II speech-understanding system (HSII) (Lesser et al [11], Fennell [9], and Erman and Lesser [6]) is an implementation of a knowledge-based multiprocessing artificial intelligence (AI) problem-solving organization. HSII is intended to represent a problem-solving organization which is applicable for implementation in a parallel hardware environment such as C.mmp (Bell et al [2]). The primary characteristics of this organization include: 1) multiple, diverse, independent and asynchronously executing knowledge sources (KS's), 2) cooperating (in terms of control) via a generalized form of the hypothesize-and-test paradigm involving the data-directed invocation of KS processes, and 3) communicating (in terms of data) via a shared blackboard-like data base in which the current data state is held in a homogeneous, multidimensional, directed-graph structure. The object of this paper is to explore several of the ramifications of such a problem-solving organization by examining the mechanisms and policies underlying HSII which are necessary for supporting its organization as a multiprocessing system. In addition, a multiprocessor simulation study is presented which details the effects of actually implementing such a parallel organization for use in a particular application area, that of speech understanding.