The paper describes a succinct problem-oriented programming language. The language is broad in scope, having been developed for, and applied effectively in, such diverse areas as microprogramming, switching theory, operations research, information retrieval, sorting theory, structure of compilers, search procedures, and language translation. The language permits a high degree of useful formalism. It relies heavily on a systematic extension of a small set of basic operations to vectors, matrices, and trees, and on a family of flexible selection operations controlled by logical vectors. Illustrations are drawn from a variety of applications.

A Programming Language

The Artificial Intelligence field continues to be plagued by what can only be described as ‘bold promises for the future syndrome’, often perpetrated by researchers who should know better. While impartial assessment can point to concrete contributions over the past 50 years (such as automated theorem proving, games strategies, the LISP and Prolog high-level computer languages, Automatic Speech Recognition, Natural Language Processing, mobile robot path planning, unmanned vehicles, humanoid robots, data mining, and more), the more cynical argue that AI has witnessed more than its fair share of ‘unmitigated disasters’ during this time – see, for example [3,58,107,125,186]. The general public becomes rapidly jaded with such ‘bold predictions’ that fail to live up to their original hype, and which ultimately render the zealots’ promises as counter-productive.

Computational Intelligence: An Introduction

Throughout the orthodox mainsteam of the development of logic in the West, the prevailing view was that every proposition is either true or else false (although which of these is the case may well neither be necessary as regards the matter itself nor determinable as regards our knowledge of it). This thesis, commonly called the ‘law of bivalence’ — constituting one key articulation of the ‘law of the excluded middle’ — was, however, already questioned in antiquity. In Ch. IX of his treatise On Interpretation (De interpretatione), Aristotle discussed of the truth-status of alternatives regarding ‘future-contingent’ matters, whose occurrence — like that of the sea-battle tomorrow — is not yet determinable by us, and may indeed actually be undetermined. His views on the matter are still disputed, but many commentators, both in antiquity and later, held him to assert that propositions about future contingents, like that asserting the occurrence of the sea-battle, are neither actually true nor actually false, but potentially either, thus having — at least prior to the event — a third, indeterminate truth-status. The acceptance of the principle of bivalence was, in antiquity, closely bound up with the doctrine of determinism. The Epicureans, who were indeterminists, rejected the law of bivalence; the Stoics (and above all Chrysippus) who were rigid determinists, insisted upon it.1

Many Valued Logic

PREFACE. FUZZY EXPERT SYSTEMS THEORY. The Evolution From Expert Systems to Fuzzy Expert Systems. General Purpose Fuzzy Expert Systems. Inferences With Inaccuracy and Uncertainty in Expert Systems. On the Representation of Relational Production Rules in Expert Systems. Reduction Procedures for Rule-Based Expert Systems as a Tool for Studies of Properties of Expert's Knowledge. The Physiology of the Expert System. On the Processing of Imperfect Information Using Structured Frameworks. Fuzzy Linguistic Inference Network Generator. Advances in Automated Reasoning Using Possibilistic Logic. Fuzzy Associative Memory Systems. APPLICATIONS OF FUZZY EXPERT SYSTEMS. The Role of Approximate Reasoning in a Medical Expert System. Fess: A Reusable Fuzzy Expert System. Design for Designing: Fuzzy Relational Environmental Design Assistant (FREDA). On the Design of a Fuzzy Intelligent Differential Equation Solver. MILORD: A Fuzzy Expert Systems Shell. Medical Decision Making Using Classification Techniques for Establishment of Knowledge Bases. Fuzzy Expert Systems for an Intelligent Computer-Based Tutor. Expert System on a Chip: An Engine for Approximate Reasoning. A Probabilistic Logic for Expert Systems. COMEX-An Autonomous Fuzzy Expert System for Tactical Communications Networks.

Fuzzy Expert Systems

https://projecteuclid.org/download/pdf_1/euclid.pja/1195522171

Jan Łukasiewicz

Papers

Aristotle's Syllogistic From the Standpoint of Modern Formal Logic

Elements of mathematical logic

A System of Modal Logic

On the intuitionistic theory of deduction