Search results for "Propositional calculus"

showing 10 items of 14 documents

Mining Interpretable Rules for Sentiment and Semantic Relation Analysis Using Tsetlin Machines

2020

Tsetlin Machines (TMs) are an interpretable pattern recognition approach that captures patterns with high discriminative power from data. Patterns are represented as conjunctive clauses in propositional logic, produced using bandit-learning in the form of Tsetlin Automata. In this work, we propose a TM-based approach to two common Natural Language Processing (NLP) tasks, viz. Sentiment Analysis and Semantic Relation Categorization. By performing frequent itemset mining on the patterns produced, we show that they follow existing expert-verified rule-sets or lexicons. Further, our comparison with other widely used machine learning techniques indicates that the TM approach helps maintain inter…

Computer sciencebusiness.industrySemantic analysis (machine learning)Sentiment analysiscomputer.software_genrePropositional calculusAutomatonComputingMethodologies_PATTERNRECOGNITIONDiscriminative modelCategorizationPattern recognition (psychology)Artificial intelligencebusinesscomputerNatural language processingInterpretability
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Obligations and Conditionals

2015

The paper considers two kinds of medieval obligational disputations (positio, rei veritas) and the medieval genre of sophismata in relation to the kinds of inferences accepted in them. The main texts discussed are the anonymous Obligationes parisienses from the early 13th century and Richard Kilvington’s Sophismata from the early 14th century. Four different kinds of warranted transition from an antecedent to a consequent become apparent in the medieval discussions: (1) the strong logical validity of basic propositional logic, (2) analytic validity based on conceptual containment, (3) merely semantic impossibility of the antecedent being true without the consequent, and (4) intuitively true…

Counterfactual thinkingMedieval philosophyHistoryCounterfactual conditionalAntecedent (logic)velvoitteetPropositional calculussophismatacounterfactualsEpistemologyseurauksetPhilosophyconditionalsvaliditeettiImpossibilityRelation (history of concept)SophismataMathematicsVivarium
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Regularly Algebraizable Logics

2001

A sentential logic (S, C) is regularly algebraizable (alias 1-algebraizable) if it possesses a non-empty system E(p, q) of equivalence sentences such that E(p, q) ⊆ C(p, q).

Discrete mathematicsAliasEquivalence (formal languages)Propositional calculusMathematics
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Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability

2020

Despite significant effort, building models that are both interpretable and accurate is an unresolved challenge for many pattern recognition problems. In general, rule-based and linear models lack accuracy, while deep learning interpretability is based on rough approximations of the underlying inference. Using a linear combination of conjunctive clauses in propositional logic, Tsetlin Machines (TMs) have shown competitive performance on diverse benchmarks. However, to do so, many clauses are needed, which impacts interpretability. Here, we address the accuracy-interpretability challenge in machine learning by equipping the TM clauses with integer weights. The resulting Integer Weighted TM (…

FOS: Computer and information sciencesBoosting (machine learning)Theoretical computer scienceinteger-weighted Tsetlin machineGeneral Computer ScienceComputer scienceComputer Science - Artificial Intelligence0206 medical engineeringNatural language understandingInference02 engineering and technologycomputer.software_genre0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceTsetlin machineVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550InterpretabilityArtificial neural networkLearning automatabusiness.industryDeep learningGeneral Engineeringinterpretable machine learningrule-based learninginterpretable AIPropositional calculusSupport vector machineArtificial Intelligence (cs.AI)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESXAIPattern recognition (psychology)020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligencebusinesslcsh:TK1-9971computer020602 bioinformaticsInteger (computer science)
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On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators

2020

The Tsetlin Machine (TM) is a recent machine learning algorithm with several distinct properties, such as interpretability, simplicity, and hardware-friendliness. Although numerous empirical evaluations report on its performance, the mathematical analysis of its convergence is still open. In this article, we analyze the convergence of the TM with only one clause involved for classification. More specifically, we examine two basic logical operators, namely, the "IDENTITY"- and "NOT" operators. Our analysis reveals that the TM, with just one clause, can converge correctly to the intended logical operator, learning from training data over an infinite time horizon. Besides, it can capture arbit…

FOS: Computer and information sciencesComputer Science - Machine LearningTraining setLearning automataComputer Science - Artificial IntelligenceComputer sciencebusiness.industryApplied MathematicsTime horizonPropositional calculusLogical connectiveMachine Learning (cs.LG)Artificial Intelligence (cs.AI)Operator (computer programming)Computational Theory and MathematicsArtificial IntelligencePattern recognition (psychology)Convergence (routing)Identity (object-oriented programming)Computer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareInterpretabilityIEEE Transactions on Pattern Analysis and Machine Intelligence
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From Arithmetic to Logic based AI: A Comparative Analysis of Neural Networks and Tsetlin Machine

2020

Neural networks constitute a well-established design method for current and future generations of artificial intelligence. They depends on regressed arithmetic between perceptrons organized in multiple layers to derive a set of weights that can be used for classification or prediction. Over the past few decades, significant progress has been made in low-complexity designs enabled by powerful hardware/software ecosystems. Built on the foundations of finite-state automata and game theory, Tsetlin Machine is increasingly gaining momentum as an emerging artificial intelligence design method. It is fundamentally based on propositional logic based formulation using booleanized input features. Rec…

Hardware architectureArtificial neural networkLearning automataComputer science020208 electrical & electronic engineering02 engineering and technologyEnergy consumptionPerceptronPropositional calculus020202 computer hardware & architectureAutomaton0202 electrical engineering electronic engineering information engineeringArithmeticEfficient energy use2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)
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A Tsetlin Machine with Multigranular Clauses

2019

The recently introduced Tsetlin Machine (TM) has provided competitive pattern recognition accuracy in several benchmarks, however, requires a 3-dimensional hyperparameter search. In this paper, we introduce the Multigranular Tsetlin Machine (MTM). The MTM eliminates the specificity hyperparameter, used by the TM to control the granularity of the conjunctive clauses that it produces for recognizing patterns. Instead of using a fixed global specificity, we encode varying specificity as part of the clauses, rendering the clauses multigranular. This makes it easier to configure the TM because the dimensionality of the hyperparameter search space is reduced to only two dimensions. Indeed, it tur…

HyperparameterLearning automataComputer sciencebusiness.industrySupervised learningPattern recognitionGranularityArtificial intelligenceENCODEPropositional calculusbusinessRendering (computer graphics)Curse of dimensionality
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Measuring the Novelty of Natural Language Text Using the Conjunctive Clauses of a Tsetlin Machine Text Classifier

2020

Most supervised text classification approaches assume a closed world, counting on all classes being present in the data at training time. This assumption can lead to unpredictable behaviour during operation, whenever novel, previously unseen, classes appear. Although deep learning-based methods have recently been used for novelty detection, they are challenging to interpret due to their black-box nature. This paper addresses \emph{interpretable} open-world text classification, where the trained classifier must deal with novel classes during operation. To this end, we extend the recently introduced Tsetlin machine (TM) with a novelty scoring mechanism. The mechanism uses the conjunctive clau…

I.2FOS: Computer and information sciencesComputer Science - Machine LearningI.5Computer Science - Artificial IntelligenceComputer scienceI.2; I.5; I.7computer.software_genreI.7Novelty detectionMeasure (mathematics)Machine Learning (cs.LG)Representation (mathematics)Computer Science - Computation and Languagebusiness.industryDeep learningNoveltyPropositional calculusArtificial Intelligence (cs.AI)Artificial intelligencebusinessClassifier (UML)computerComputation and Language (cs.CL)Natural language processingNatural language
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Logical Sentential Calculi Inspired by the Chrysippean Sentential Calculus

2021

The aim of the present paper is to consider an approach, different from that presented by J. Łukasiewicz, concerning the interpretation of the so-called stoic undemonstrables, which were given by Chrysippus. Stoic undemonstrables have been interpreted in two different ways: using the notion of “negation of a sentence” (Łukasiewicz) and using the notion of “a sentence inconsistent with a given one” (Mates). According to the Stoics, two sentences are inconsistent if one of them is negation of the other. The Mates’ interpretation generates five different inference rules. Based on one of these rules we can consider (with other undemonstrables) four different stoic propositional calculi. Taking …

Interpretation (logic)Deductive reasoningComputer science010102 general mathematics06 humanities and the arts0603 philosophy ethics and religionPropositional calculus01 natural sciencesLinguisticsFragment (logic)Negation060302 philosophy0101 mathematicsRule of inferenceSentence
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The Regression Tsetlin Machine: A Tsetlin Machine for Continuous Output Problems

2019

The recently introduced Tsetlin Machine (TM) has provided competitive pattern classification accuracy in several benchmarks, composing patterns with easy-to-interpret conjunctive clauses in propositional logic. In this paper, we go beyond pattern classification by introducing a new type of TMs, namely, the Regression Tsetlin Machine (RTM). In all brevity, we modify the inner inference mechanism of the TM so that input patterns are transformed into a single continuous output, rather than to distinct categories. We achieve this by: (1) using the conjunctive clauses of the TM to capture arbitrarily complex patterns; (2) mapping these patterns to a continuous output through a novel voting and n…

Normalization (statistics)Scheme (programming language)Computer scienceInferenceProbability density function02 engineering and technologyPropositional calculusRegression020202 computer hardware & architecturePattern recognition (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingNoise (video)Algorithmcomputercomputer.programming_language
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