Concept

Reasoning system

Résumé
In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play an important role in the implementation of artificial intelligence and knowledge-based systems. By the everyday usage definition of the phrase, all computer systems are reasoning systems in that they all automate some type of logic or decision. In typical use in the Information Technology field however, the phrase is usually reserved for systems that perform more complex kinds of reasoning. For example, not for systems that do fairly straightforward types of reasoning such as calculating a sales tax or customer discount but making logical inferences about a medical diagnosis or mathematical theorem. Reasoning systems come in two modes: interactive and batch processing. Interactive systems interface with the user to ask clarifying questions or otherwise allow the user to guide the reasoning process. Batch systems take in all the available information at once and generate the best answer possible without user feedback or guidance. Reasoning systems have a wide field of application that includes scheduling, business rule processing, problem solving, complex event processing, intrusion detection, predictive analytics, robotics, computer vision, and natural language processing. The first reasoning systems were theorem provers, systems that represent axioms and statements in First Order Logic and then use rules of logic such as modus ponens to infer new statements. Another early type of reasoning system were general problem solvers. These were systems such as the General Problem Solver designed by Newell and Simon. General problem solvers attempted to provide a generic planning engine that could represent and solve structured problems. They worked by decomposing problems into smaller more manageable sub-problems, solving each sub-problem and assembling the partial answers into one final answer.
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Publications associées (40)

Monotonicity Reasoning in the Age of Neural Foundation Models

Zeming Chen, Qiyue Gao

The recent advance of large language models (LLMs) demonstrates that these large-scale foundation models achieve remarkable capabilities across a wide range of language tasks and domains. The success of the statistical learning approach challenges our unde ...
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Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture

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With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is ...
IOS PRESS2022

A Data-Knowledge Hybrid Driven Method for Gas Turbine Gas Path Diagnosis

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Gas path fault diagnosis of a gas turbine is a complex task involving field data analysis and knowledge-based reasoning. In this paper, a data-knowledge hybrid driven method for gas path fault diagnosis is proposed by integrating a physical model-based gas ...
MDPI2022
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Unités associées (1)
Concepts associés (4)
Knowledge-based systems
A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. The term is broad and refers to many different kinds of systems. The one common theme that unites all knowledge based systems is an attempt to represent knowledge explicitly and a reasoning system that allows it to derive new knowledge. Thus, a knowledge-based system has two distinguishing features: a knowledge base and an inference engine.
Cadre (intelligence artificielle)
Le terme de cadres (en anglais frames) a été proposé par Marvin Minsky dans son article de 1974 intitulé A Framework for Representing Knowledge. Un cadre en intelligence artificielle est une structure de données utilisée pour subdiviser la connaissance en sous-structures représentant des situations stéréotypées. Les cadres sont reliés entre eux pour former une idée complète. Un cadre contient de l'information sur la manière d'utiliser le cadre, sur ce qu'on peut en attendre, et sur ce qu'on peut faire lorsque cette attente n'est pas satisfaite.
Système expert
Un système expert est un outil capable de reproduire les mécanismes cognitifs d'un expert, dans un domaine particulier. Il s'agit de l'une des voies tentant d'aboutir à l'intelligence artificielle. Plus précisément, un système expert est un logiciel capable de répondre à des questions, en effectuant un raisonnement à partir de faits et de règles connues. Il peut servir notamment comme outil d'aide à la décision. Le premier système expert a été Dendral. Il permettait d'identifier les constituants chimiques.
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Cours associés (1)
CS-330: Artificial intelligence
Introduction aux techniques de l'Intelligence Artificielle, complémentée par des exercices de programmation qui montrent les algorithmes et des exemples de leur application à des problèmes pratiques.
Séances de cours associées (16)
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Explore le raisonnement incertain, les réseaux bayésiens et la résolution stochastique, soulignant l'importance de la logique probabiliste et de l'enlèvement.
Logique proposée : Règles d'inférence
Couvre l'interprétation de la logique de proposition et des règles d'inférence pour l'implication, la conjonction et la double négation.
Logique propositionnelle : règles d'inférence et arguments valides
Couvre les règles d'inférence dans la logique propositionnelle et les sophismes logiques communs.
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