No description available.

No description available.

No description available.

Reproduction de : Thèse de doctorat : informatique : Grenoble, INPG : 1989. / Titre provenant de l'écran-titre. Bibliogr. p. 161-177.

Habilitation à diriger des recherches : Informatique : Rennes 1 : 1998. / Bibliogr. p.143-158.

Report (M.S.)--Virginia Polytechnic Institute and State University. M.S. 1991. / Abstract. Includes bibliographical references (leaves 80-81). Also available via the Internet.

Diss.--Philosophische Fakultät I--Universität Zürich, 1993/1994. / Bibliogr. p. 170-175.

[pt] As arquiteturas convencionais de computadores, baseadas no modelo de Von Neumann, não implementam eficientemente a linguagem Prolog, fundamentada em mecanismos de unificação e retrocesso automático. Este trabalho propõe a arquitetura de um acelerador, baseado a uma máquina virtual Prolog (PLM) desenvolvida na COPPE/UFRJ. A arquitetura proposta aumenta a eficiência da máquina virtual explorando o paralelismo da memória associativa na realização do mecanismo de retrocesso. O impacto no desempenho da máquina virtual decorrente da nova arquitetura foi avaliado por simulação utilizando programas clássicos encontrados na literatura. / [en] Conventional computer architectures based on Von Neumann’s model do not efficiently implement the Prolog language, founded on unification and automatic backtracking mechanisms. This work presents the architecture of a content addressable memory accelerator to be connected to a Prolog Virtual machine (PLM) developed at COPPE/UFRJ. The presented architecture increases the virtual machine’s efficiency by exploring the content addressable memory’s parallelism to implement the backtracking mechanism. The impact on the virtual machine’s performance due to the new architecture was evaluated by simulation, using classical programs found on the literature.

Many expert systems have been developed over the past decades. ProGrammar is a modest expert system shell that has been developed recently. It is built on top of the CProlog/UNIX* system running on a VAX† 11/750. ProGrammar is designed for processing and developing grammars. It can also be used as a knowledge base constructor for other fields besides grammars, a learning tool, a Prolog interpreter, and as a consulting system. ProGrammar is an interactive system meaning not only can the user query ProGrammar but ProGrammar also can question the user. The user is allowed to request an explanation from the ProGrammar on how the solution to the query was derived. / Science, Faculty of / Computer Science, Department of / Graduate

DLOG is a logic-based data model developed to show how logic-programming can combine contributions of Data Base Management (DBM) and Artificial Intelligence (AI). The DLOG specification includes a language syntax, a proof (or query evaluation) procedure, a description of the language's semantics, and a specification of the relationships between assertions, queries, and application databases. DLOG's data description language is the Horn clause subset of first order logic [Kowalski79, Kowalski81], augmented with descriptive terms and non-Horn integrity constraints. The descriptive terms are motivated by AI representation language ideas, specifically, the descriptive terms of the KRL language [Bobrow77]. A similar facility based on logical descriptions is provided in DLOG. DLOG permits the use of definite and indefinite descriptions of individuals and sets in queries and assertions. The meaning of DLOG's extended language is specified as Horn clauses that describe the relation between the basic language and the extensions. The experimental implementation is a Prolog program derived from that specification. The DLOG implementation relies on an extension to the standard Prolog proof procedure. This includes a "unification" procedure that matches embedded terms by recursively invoking the DLOG proof procedure (cf. LOGLISP [Robinson82]). The experimental system includes Prolog implementations of traditional database facilities (e.g., transactions, integrity constraints, data dictionaries, data manipulation language facilities), and an idea for using logic as the basis for heuristic interpretation of queries. This heuristic uses a notion of partial, match or sub-proof to produce assumptions under which plausible query answers can be derived. The experimental DLOG knowledge base management system is exercised by describing an undergraduate degree program. The example application is a description of the Bachelor of Computer Science degree requirements at The University of British Columbia. This application demonstrates how DLOG's descriptive terms provide a concise description of degree program knowledge, and how that knowledge is used to specify student programs and select program options. / Science, Faculty of / Computer Science, Department of / Graduate