Analogical Proportions: Why They Are Useful in AI

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2021/621 ◽

2021 ◽

Author(s):

Henri Prade ◽

Gilles Richard

Keyword(s):

Artificial Intelligence ◽

Image Processing ◽

Computational Linguistics ◽

Analogical Reasoning ◽

Formal Modeling ◽

Preference Learning ◽

Case Based Reasoning ◽

Inference Mechanism ◽

Formal Concepts ◽

Case Based

This paper presents a survey of researches in analogical reasoning whose building block are analogical proportions which are statements of the form “a is to b as c is to d”. They have been developed in the last twenty years within an Artificial Intelligence perspective. After discussing their formal modeling with the associated inference mechanism, the paper reports the main results obtained in various AI domains ranging from computational linguistics to classification, including image processing, I.Q. tests, case based reasoning, preference learning, and formal concepts analysis. The last section discusses some new theoretical concerns, and the potential of analogical proportions in other areas such as argumentation, transfer learning, and XAI.

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Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽

10.24160/1993-6982-2020-5-132-139 ◽

2020 ◽

Vol 5 (5) ◽

pp. 132-139

Author(s):

Ivan E. Kurilenko ◽

◽

Igor E. Nikonov ◽

Keyword(s):

Artificial Intelligence ◽

Classification Problem ◽

Subject Area ◽

Text Messages ◽

Case Based Reasoning ◽

Short Text ◽

Proposed Modification ◽

Voice Interaction ◽

Text Content ◽

Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

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Retrieving Assembly Part Design Using Case-Based Reasoning and Genetic Algorithms

Manufacturing Engineering and Materials Handling, Parts A and B ◽

10.1115/imece2005-80334 ◽

2005 ◽

Cited By ~ 1

Author(s):

Guanghsu A. Chang ◽

Cheng-Chung Su ◽

John W. Priest

Keyword(s):

Artificial Intelligence ◽

Genetic Algorithms ◽

Nearest Neighbor ◽

Similarity Measures ◽

Experimental Results ◽

Case Based Reasoning ◽

Feature Weight ◽

Similar Part ◽

Case Base ◽

Case Based

Artificial intelligence (AI) approaches have been successfully applied to many fields. Among the numerous AI approaches, Case-Based Reasoning (CBR) is an approach that mainly focuses on the reuse of knowledge and experience. However, little work is done on applications of CBR to improve assembly part design. Similarity measures and the weight of different features are crucial in determining the accuracy of retrieving cases from the case base. To develop the weight of part features and retrieve a similar part design, the research proposes using Genetic Algorithms (GAs) to learn the optimum feature weight and employing nearest-neighbor technique to measure the similarity of assembly part design. Early experimental results indicate that the similar part design is effectively retrieved by these similarity measures.

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A NEW APPROACH FOR IMPROVING BUSINESS PERFORMANCE USING ARTIFICIAL INTELLIGENCE AND CASE-BASED REASONING

Decision Making Systems in Business Administration - World Scientific Proceedings Series on Computer Engineering and Information Science ◽

10.1142/9789814452052_0015 ◽

2012 ◽

pp. 163-184

Author(s):

ALEKSANDAR VUJOVIC ◽

ZDRAVKO KRIVOKAPIC ◽

MIRKO SOKOVIC ◽

SLAVKO ARSOVSKI ◽

MARC ARTHUR DIAYE ◽

...

Keyword(s):

Artificial Intelligence ◽

Business Performance ◽

Case Based Reasoning ◽

New Approach ◽

Case Based

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Cyber Physical Control Systems

Challenges, Opportunities, and Dimensions of Cyber-Physical Systems - Advances in Systems Analysis, Software Engineering, and High Performance Computing ◽

10.4018/978-1-4666-7312-0.ch014 ◽

2015 ◽

pp. 263-285

Keyword(s):

Artificial Intelligence ◽

Control Systems ◽

Intelligent Systems ◽

Control Strategies ◽

Case Based Reasoning ◽

Physical Control ◽

Closed Loop Systems ◽

Intelligence Models ◽

Algorithmic Design ◽

Case Based

The focus of algorithmic design is to solve composite problems. Intelligent systems use intellectual concepts like evolutionary computation, artificial neural networks, fuzzy systems, and swarm intelligence to process natural intelligence models. Artificial intelligence is used as a part of intelligent systems to perform logic- and case-based reasoning. Systems like mechanical and electrical support systems are operated by utilizing Supervisory Control and Data Acquisition (SCADA) systems. These systems cannot accomplish their purpose, provided the control system deals with the reliability of it. In CPSs, dimensions of physical processes are taken by sensors and are processed in cyber subsystems to drive the actuators that affect the physical processors. CPSs are closed-loop systems. The adaptation and the prediction are the properties to be followed by the control strategies that are implemented in cyber subsystems. This chapter explores cyber physical control systems.

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Individual Prognosis of Diabetes Long-term Risks: A CBR Approach

Methods of Information in Medicine ◽

10.1055/s-0038-1634463 ◽

2001 ◽

Vol 40 (01) ◽

pp. 46-51 ◽

Cited By ~ 18

Author(s):

A. Palaudàries ◽

E. Plaza ◽

E. Armengol

Keyword(s):

Artificial Intelligence ◽

Diabetic Complication ◽

Diabetic Patients ◽

Case Based Reasoning ◽

Artificial Intelligence Technique ◽

Past Experiences ◽

Risk Pattern ◽

Case Based ◽

Intelligence Technique

AbstractWe present DIRAS, an application to support physicians in determining the risk of complications for individual diabetic patients. The risk pattern of each diabetic patient is obtained using a Case-based Reasoning method called LID. Case-based Reasoning is an Artificial Intelligence technique based on solving new situations according to past experiences. For each patient, the LID method determines the risk of each diabetic complication according to the risk of already diagnosed patients. In addition, LID builds a description that can be viewed as an explanation of the obtained risk.

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A Case-Based Reasoning Approach for the Cybersecurity Incident Recording and Resolution

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s021819401940014x ◽

2019 ◽

Vol 29 (11n12) ◽

pp. 1607-1627

Author(s):

Raul Ceretta Nunes ◽

Marcelo Colomé ◽

Fabio André Barcelos ◽

Marcelo Garbin ◽

Gustavo Bathu Paulus ◽

...

Keyword(s):

Artificial Intelligence ◽

Problem Solving ◽

Case Based Reasoning ◽

Intelligent Computing ◽

Resolution System ◽

Concrete Problem ◽

Different Types ◽

Practice Knowledge ◽

Resolution Data ◽

Case Based

Intelligent computing techniques have a paramount importance to the treatment of cybersecurity incidents. In such Artificial Intelligence (AI) context, while most of the algorithms explored in the cybersecurity domain aim to present solutions to intrusion detection problems, these algorithms seldom approach the correction procedures that are explored in the resolution of cybersecurity incident problems that already took place. In practice, knowledge regarding cybersecurity resolution data and procedures is being under-used in the development of intelligent cybersecurity systems, sometimes even lost and not used at all. In this context, this work proposes the Case-based Cybersecurity Incident Resolution System (CCIRS), a system that implements an approach to integrate case-based reasoning (CBR) techniques and the IODEF standard in order to retain concrete problem-solving experiences of cybersecurity incident resolution to be reused in the resolution of new incidents. Different types of experimental results so far obtained with the CCIRS show that information security knowledge can be retained with our approach in a reusable memory improving the resolution of new cybersecurity problems.

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Artificial Intelligence-Virtual Trainer: An educative system based on artificial intelligence and designed to produce varied and consistent training lessons

Proceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology ◽

10.1177/1754337116651013 ◽

2016 ◽

Vol 231 (2) ◽

pp. 110-124 ◽

Cited By ~ 4

Author(s):

Julien Henriet

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Ordered Set ◽

Case Based Reasoning ◽

Adaptation Process ◽

Multi Agent System ◽

Multi Agent ◽

Different Parts ◽

Case Based ◽

Underlying Theme

AI-Virtual Trainer is an educative system using Artificial Intelligence to propose varied lessons to trainers. The agents of this multi-agent system apply case-based reasoning to build solutions by analogy. However, as required by the field, Artificial Intelligence-Virtual Trainer never proposes the same lesson twice, whereas the same objective may be set many times consecutively. The adaptation process of Artificial Intelligence-Virtual Trainer delivers an ordered set of exercises adapted to the objectives and sub-objectives chosen by trainers. This process has been enriched by including the notion of distance between exercises: the proposed tasks are not only appropriate but are hierarchically ordered. With this new version of the system, students are guided towards their objectives via an underlying theme. Finally, the agents responsible for the different parts of lessons collaborate with each other according to a dedicated protocol and decision-making policy since no exercise must appear more than once in the same lesson. The results prove that Artificial Intelligence-Virtual Trainer, however perfectible, meets the requirements of this field.

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Sistem Cerdas Permainan Papan The Battle Of Honor dengan Decision Making dan Machine Learning

Jurnal Buana Informatika ◽

10.24002/jbi.v12i2.4905 ◽

2021 ◽

Vol 12 (2) ◽

pp. 136

Author(s):

Arnan Dwika Diasmara ◽

Aditya Wikan Mahastama ◽

Antonius Rachmat Chrismanto

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Decision Making ◽

Intelligent System ◽

Third Party ◽

Case Based Reasoning ◽

Board Game ◽

Rule Based ◽

Case Based ◽

Rule Based Systems

Abstract. Intelligent System of the Battle of Honor Board Game with Decision Making and Machine Learning. The Battle of Honor is a board game where 2 players face each other to bring down their opponent's flag. This game requires a third party to act as the referee because the players cannot see each other's pawns during the game. The solution to this is to implement Rule-Based Systems (RBS) on a system developed with Unity to support the referee's role in making decisions based on the rules of the game. Researchers also develop Artificial Intelligence (AI) as opposed to applying Case-Based reasoning (CBR). The application of CBR is supported by the nearest neighbor algorithm to find cases that have a high degree of similarity. In the basic test, the results of the CBR test were obtained with the highest formulated accuracy of the 3 examiners, namely 97.101%. In testing the AI scenario as a referee, it is analyzed through colliding pieces and gives the right decision in determining victoryKeywords: The Battle of Honor, CBR, RBS, unity, AIAbstrak. The Battle of Honor merupakan permainan papan dimana 2 pemain saling berhadapan untuk menjatuhkan bendera lawannya. Permainan ini membutuhkan pihak ketiga yang berperan sebagai wasit karena pemain yang saling berhadapan tidak dapat saling melihat bidak lawannya. Solusi dari hal tersebut yaitu mengimplementasikan Rule-Based Systems (RBS) pada sistem yang dikembangkan dengan Unity untuk mendukung peran wasit dalam memberikan keputusan berdasarkan aturan permainan. Peneliti juga mengembangkan Artificial Intelligence (AI) sebagai lawan dengan menerapkan Case-Based reasoning (CBR). Penerapan CBR didukung dengan algoritma nearest neighbour untuk mencari kasus yang memiliki tingkat kemiripan yang tinggi. Pada pengujian dasar didapatkan hasil uji CBR dengan accuracy yang dirumuskan tertinggi dari 3 penguji yaitu 97,101%. Pada pengujian skenario AI sebagai wasit dianalisis lewat bidak yang bertabrakan dan memberikan keputusan yang tepat dalam menentukan kemenangan.Kata Kunci: The Battle of Honor, CBR, RBS, unity, AI

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Diagnosis of Simplex Herpes by Case-Based Reasoning Method

SinkrOn ◽

10.33395/sinkron.v4i1.10151 ◽

2019 ◽

Vol 4 (1) ◽

pp. 58

Author(s):

Hari Marfalino ◽

Dinda Djesmedi ◽

Afandi Iddil Filresi

Keyword(s):

Artificial Intelligence ◽

Herpes Simplex ◽

Expert System ◽

Venereal Disease ◽

Initial Diagnosis ◽

Previous Experience ◽

Case Based Reasoning ◽

Appropriate Treatment ◽

Case Based

Artificial Intelligence (Artificial Intelligence or AI) is defined as the intelligence shown by an artificial entity. Such systems are generally considered computers. Intelligence is created and incorporated into a machine (computer) so that it can do work as humans can. Artificial Intelligence (Artificial Intelligence or AI) is defined as intelligence shown by an artificial entity. Such systems are generally considered computers. Intelligence is created and incorporated into a machine (computer) so that it can do work like humans can. CBR method is a method used to solve a problem by using previous experience to solve a new problem. This research will discuss about Herpes Simplex, a venereal disease. In implementing this expert system, it is used by families of patients with Herpes Simplex. The goal is that the expert system can assist the patient's family in conducting the initial diagnosis process to determine the symptoms felt by sufferers of Herpes Simplex. And with the existence of this expert system can carry out appropriate treatment by sufferers of Herpes Simplex.

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