936 resultados para Object-oriented programming (Computer science)


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Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

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Neu-Model, an ongoing project aimed at developing a neural simulation environment that is extremely computationally powerful and flexible, is described. It is shown that the use of good Software Engineering techniques in Neu-Model’s design and implementation is resulting in a high performance system that is powerful and flexible enough to allow rigorous exploration of brain function at a variety of conceptual levels.

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Tutkielma käsittelee nykyisiä kognitiotieteen teorioita käsitteistä ja niiden mallintamista oliokeskeisillä tietämyksen esittämisen menetelmillä. Käsiteteorioista käsitellään klassinen, määritelmäteoria, prototyyppiteoria, duaaliteoriat, uusklassinen teoria, teoria-teoria ja atomistinen teoria. Oliokeskeiset menetelmät ovat viime aikoina jakautuneet kahden tyyppisiin kieliin: oliopohjaisiin ja luokkapohjaisiin. Uudet olio-pohjaiset olio-ohjelmointikielet antavat käsitteiden representointiin mahdollisuuksia, jotka puuttuvat aikaisemmista luokka-pohjaisista kielistä ja myös kehysmenetelmistä. Tutkielma osoittaa, että oliopohjaisten kielten uudet piirteet tarjoavat keinoja, joilla käsitteitä voidaan esittää symbolisessa muodossa paremmin kuin perinteisillä menetelmillä. Niillä pystytään simuloimaan kaikkea mitä luokkapohjaisilla kielillä voidaan, mutta ne pystyvät lisäksi simuloimaan perheyhtäläisyyskäsitteitä ja mahdollistavat olioiden dynaamisen muuttamisen ilman, että siinä rikotaan psykologisen essentialismin periaatetta. Tutkielma osoittaa lisäksi vakavia puutteitta, jotka koskevat koko oliokeskeistä menetelmää. Avainsanat: käsitteet, käsiteteoriat, tekoäly, komputationaalinen psykologia, olio-ohjelmointi, tiedon esittäminen

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Indian logic has a long history. It somewhat covers the domains of two of the six schools (darsanas) of Indian philosophy, namely, Nyaya and Vaisesika. The generally accepted definition of Indian logic over the ages is the science which ascertains valid knowledge either by means of six senses or by means of the five members of the syllogism. In other words, perception and inference constitute the subject matter of logic. The science of logic evolved in India through three ages: the ancient, the medieval and the modern, spanning almost thirty centuries. Advances in Computer Science, in particular, in Artificial Intelligence have got researchers in these areas interested in the basic problems of language, logic and cognition in the past three decades. In the 1980s, Artificial Intelligence has evolved into knowledge-based and intelligent system design, and the knowledge base and inference engine have become standard subsystems of an intelligent system. One of the important issues in the design of such systems is knowledge acquisition from humans who are experts in a branch of learning (such as medicine or law) and transferring that knowledge to a computing system. The second important issue in such systems is the validation of the knowledge base of the system i.e. ensuring that the knowledge is complete and consistent. It is in this context that comparative study of Indian logic with recent theories of logic, language and knowledge engineering will help the computer scientist understand the deeper implications of the terms and concepts he is currently using and attempting to develop.

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Tesis leida en la Universidad de Aberdeen. 178 p.

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This report is an introduction to the concept of treewidth, a property of graphs that has important implications in algorithms. Some basic concepts of graph theory are presented in the first chapter for those readers that are not familiar with the notation. In Chapter 2, the definition of treewidth and some different ways of characterizing it are explained. The last two chapters focus on the algorithmic implications of treewidth, which are very relevant in Computer Science. An algorithm to compute the treewidth of a graph is presented and its result can be later applied to many other problems in graph theory, like those introduced in the last chapter.