Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia Elétrica. / Made available in DSpace on 2013-06-25T22:50:29Z (GMT). No. of bitstreams: 1 309674.pdf: 1806560 bytes, checksum: 7cc8bf337e22414d7a92c932dea66e05 (MD5) / Este trabalho apresenta o aprimoramento da ferramenta Shell Intellec System, para a criação automática de Sistemas Especialistas, com a utilização de fatores de certeza para tratamento da incerteza. A máquina de inferência foi desenvolvida em Prolog por se tratar de uma linguagem de programação lógica, utilizando a ferramenta Visual Prolog. A incerteza sobre o conhecimento do domínio é representada por fatores de certeza. Na shell as variáveis podem ser linguísticas, numérica e multimídia, como imagens e vídeos. A interface gráfica com o usuário foi remodelada e transcrita utilizando a ferramenta Borland C++ Builder para melhor integração com o usuário e a máquina de inferência PROLOG. Testes foram realizados para assegurar que os resultados apresentados pela Shell são compatíveis com aqueles da versão anterior. Foi realizada, também, uma avaliação sobre usabilidade da Shell por meio de um questionário chamado QUISS, baseado na norma ISO/IEC 9126, através de aplicação a um grupo de alunos, obtendo-se resultados promissores para interface desenvolvida. / This work presents the improvement of shell program Intellec System for the automatic creation of expert systems with the use of certainty factors for the treatment of uncertainty. The inference engine was developed in Prolog because it is a logic programming language, Visual Prolog using the program. Uncertainty about the domain knowledge is represented by certainty factors. In the shell variables can be linguistic, numerical and multimedia such as images and videos. The graphical user interface has been redesigned and transcribed using the tool Borland C++ Builder for better integration with the user and the PROLOG inference engine. Tests were performed to ensure that the results presented by this shell are compatible with those of the previous version. It was also performed an evaluation of usability of the shell through a questionnaire called QUISS, based on the ISO / IEC 9126, by application to a group of students, yielding good results for interfacing developed for this shell.

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Engenharia Elétrica / Made available in DSpace on 2013-07-16T01:04:13Z (GMT). No. of bitstreams: 1 213403.pdf: 2206733 bytes, checksum: 3a90080ecfa9a0b6e184c548b2b4cabc (MD5) / Este trabalho apresenta o desenvolvimento de uma shell, chamada de Intellec, para a geração automática de Sistemas Especialistas, utilizando lógica fuzzy para tratamento da incerteza. Esta shell utiliza a linguagem Prolog para a implementação da máquina de inferência, por se tratar de uma linguagem de programação lógica. A lógica fuzzy foi escolhida para representar a incerteza a respeito do conhecimento do domínio, permitindo também o uso de variáveis lingüísticas. A interface gráfica com o usuário foi implementada utilizando-se a ferramenta Borland Delphi. A validação do sistema proposto foi feita através de comparação direta entre o Intellec e o Expert SINTA, shell desenvolvida pelo grupo SINTA da Universidade Federal do Ceará, a qual é amplamente utilizada e reconhecida. Dois problemas, de áreas de conhecimento bastante distintas, foram implementados simultaneamente em ambas as shell's e os resultados obtidos foram compatíveis.

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. / Made available in DSpace on 2012-10-18T08:52:40Z (GMT). No. of bitstreams: 0Bitstream added on 2014-09-25T21:39:07Z : No. of bitstreams: 1 177741.pdf: 12891386 bytes, checksum: 366448ef7be6d7e50f2eeda77bf45563 (MD5)

There are two symmetrical resolution rules applicable to logic programs - SL-resolution which yields a top-down refutation and unit-resolution which yields a bottom-up refutation. Both resolution principles need to be coupled with a search rule before they can be used in practice. The search rule determines in which order program clauses are used in the refutation and affects both performance, completeness and quality of solutions. The thesis surveys exhaustive and heuristic search rules for SL-resolution and transformation techniques for (general) logic programs that makes unit-resolution goal oriented. The search rules were implemented as meta-interpreters for Prolog and were benchmarked on a suite of programs incorporating both deterministic and nondeterministic code. Whenever deemed applicable benchmark programs were permuted with respect to clause and goal ordering to see if it affected the interpreters performance and termination. With the help of the evaluation the conclusion was that alternative search rules for SL-resolution should not be used for performance gains but can in some cases greatly improve the quality of solutions, e.g. in planning or other applications where the quality of an answer correlates with the length of the refutation. It was also established that A* is more flexible than exhaustive search rules since its behavior can be fine-tuned with weighting, and can in some cases be more efficient than both iterative deepening and breadth-first search. The bottom-up interpreter based on unit-resolution and magic transformation had several advantages over the top-down interpreters. Notably for programs where subgoals are recomputed many times. The great disparity in implementation techniques made direct performance comparisons hard however, and it is not clear if even an optimized bottom-up interpreter is competitive against a top-down interpreter with tabling of answers.

PrologPF is a parallelising compiler targeting a distributed system of general purpose workstations connected by a relatively low performance network. The source language extends standard Prolog with the integration of higher-order functions. The execution of a compiled PrologPF program proceeds in a similar manner to standard Prolog, but uses oracles in one of two modes. An oracle represents the sequence of clauses used to reach a given point in the problem search tree, and the same PrologPF executable can be used to build oracles, or follow oracles previously generated. The parallelisation strategy used by PrologPF proceeds in two phases, which this research shows can be interleaved. An initial phase searches the problem tree to a limited depth, recording the discovered incomplete paths. In the second phase these paths are allocated to the available processors in the network. Each processor follows its assigned paths and fully searches the referenced subtree, sending solutions back to a control processor. This research investigates the use of the technique with a one-time partitioning of the problem and no further scheduling communication, and with the recursive application of the partitioning technique to effect dynamic work reassignment. For a problem requiring all solutions to be found, execution completes when all the distributed processors have completed the search of their assigned subtrees. If one solution is required, the execution of all the path processors is terminated when the control processor receives the first solution. The presence of the extra-logical Prolog predicate cut in the user program conflicts with the use of oracles to represent valid open subtrees. PrologPF promotes the use of higher-order functional programming as an alternative to the use of cut. The combined language shows that functional support can be added as a consistent extension to standard Prolog.

Context-aware computing requires software that can adapt to changes in context. When contextual circumstances trigger multiple adaptations, software must also understand the relationships between these adaptations and react according to the rules governing these relationships. Adaptable software needs a means to establish and interpret these rules in order to avoid any undesirable and potentially catastrophic conflicts. This dissertation designs and implements the Adaptation Rules Management API (ArmAPI). ArmAPI has been demonstrated to work with a Context-Oriented Programming variation for Java called ContextJ* to execute conflict-free adaptations in two software applications. ArmAPI allows programmers to define relationship types between adaptations, and transfers these definitions to Prolog facts and rules. The Prolog engine, encapsulated within ArmAPI, then works with imperative algorithms to determine the appropriate adaptations to execute based on the current set of facts, rules, and contextual circumstances. Context represents all of the conditions for all of the entities known to an observing device. In any environment, context represents a large amount of data that can influence a multitude of conflicting adaptations. This research provides an incremental step towards overcoming the problem of adaptation conflict by constructing an API that considers the relationship types of inclusion, exclusion, ordering, conditional dependency, and independence. The API has been validated via two prototypes that provide typical scenarios.

This Master's deals with the implementation of the interpreter of logic programming language "Prolog". It summarises the different approaches to evaluation of programs in thislanguage with focus on description of The Warren Abstract Machine. A new way of integratingProlog into The Microsoft .NET platform has been designed as well as its connectionwith object-oriented languages. Subsequently, an interpreter and a compiler based on TheWarren Abstract Machine have been designed and implemented including the connectionto The Microsoft.NET platform.

This lever deals with the realization of the iterpreter of an Driven Agent by the PROLOG implementation. The model was used by Jason implemented in Java that interprets the language of AgentSpeak(L). For the purposes of this project, the program in AgentSpeak(L) is first converted to an internal language form. For the demonstration, one of the examples included in the Jason program, specifically "cleaning robors", was used. The interpreter can interpret the system as a FRAg and can react in the enviroment.

This lever deals with the realization of the iterpreter of an Driven Agent by the PROLOG implementation. The model was used by Jason implemented in Java that interprets the language of AgentSpeak(L). An interpreter and a program for processing agent systems in the language AgentSpeak (L) were created. This interpreter can work with multiple agents, can implement a system with an environment and use the FRAg system for interpretation. Examples of agent systems in AgentSpeak (L) were proposed to describe the functionality of the interpreter, and subsequently the advantages and disadvantages of the FRAg system were described.

This work consists in development of expert system intended for choosing appropriate method of waste processing. The software is created in VisiRule software which is built on Prolog language and is part of WinProlog 4.900 development tool. It also deals with problematics of creating of knowledge base for applications of this type and judging of suitability of possible approaches to creating an expert system for given purpose.