A Model for Control Structures for Artificial Intelligence Programming Languages

1976 ◽  
Vol C-25 (4) ◽  
pp. 347-353 ◽  
Author(s):  
Bobrow ◽  
Wegbreit
Keyword(s):  
Artificial Intelligence ◽  
Programming Languages ◽  
Control Structures

scholarly journals Editorial. AI, Arts & Design: Questioning Learning Machines

Artnodes ◽  
2020 ◽  
Author(s):  
Ruth West ◽  
Andrés Burbano
Keyword(s):  
Artificial Intelligence ◽  
Historical Development ◽  
Machine Intelligence ◽  
Special Issue ◽  
Control Structures ◽  
Learning Machines ◽  
The Arts ◽  
Production Of Culture ◽  
The Relationship ◽  
Algorithmic Bias

Explorations of the relationship between Artificial Intelligence (AI), the arts, and design have existed throughout the historical development of AI. We are currently witnessing exponential growth in the application of Machine Learning (ML) and AI in all domains of art (visual, sonic, performing, spatial, transmedia, audiovisual, and narrative) in parallel with activity in the field that is so rapid that publication can not keep pace. In dialogue with our contemplation about this development in the arts, authors in this issue answer with questions of their own. Through questioning authorship and ethics, autonomy and automation, exploring the contribution of art to AI, algorithmic bias, control structures, machine intelligence in public art, formalization of aesthetics, the production of culture, socio-technical dimensions, relationships to games and aesthetics, and democratization of machine-based creative tools the contributors provide a multifaceted view into crucial dimensions of the present and future of creative AI. In this Artnodes special issue, we pose the question: Does generative and machine creativity in the arts and design represent an evolution of “artistic intelligence,” or is it a metamorphosis of creative practice yielding fundamentally distinct forms and modes of authorship?

Introduction to the Objects Approach in Software

2011 ◽  
pp. 1-12
Author(s):  
Peretz Shoval
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Programming Languages ◽  
Operating Systems ◽  
Object Oriented ◽  
Main Field ◽  
Analysis And Design ◽  
Development Costs ◽  
Graphical Interfaces

The term “object oriented” spread in the last decade and a half, throughout many fields of computing, including the analysis and design of information systems (IS). The use of the OO approach began in the early 1970s in fields such as computers architecture, operating systems, and artificial intelligence. But the main field to which the approach penetrated was programming languages, beginning with Simula and then with Smalltalk. Some years passed by until the approach became popular in the programming field. Reasons for the vigorous penetration of the approach include the emergence of the windows-based graphical interfaces technology, the desire to economize development costs by reusing existing software, and the transition from centralized computing to distributed- and Internet-based computing. As aforesaid, the approach penetrated into other fields of computing due to its success in the field of programming, including the field of analysis and design of IS.

Developing robot programming languages using an existing language as a base—A viewpoint

Robotica ◽  
1989 ◽  
Vol 7 (1) ◽  
pp. 71-77 ◽  
Author(s):  
S. T. Rock
Keyword(s):  
Artificial Intelligence ◽  
Programming Languages ◽  
Real Time ◽  
Programming Language ◽  
Robot Programming ◽  
Intelligent Robot ◽  
On Line

SUMMARYThe development of robot languages has followed a pattern similar to that of conventional programming languages, where robot languages have been based on an existing programming language. This paper first identifies the use of an existing base as one way of developing robot programming languages, and discusses the areas of difficulty in this approach. Then, on-line and off-line programming of robots is discussed and the requirements of robot programming languages that are different to those of non-specialised programming languages are presented. A discussion and evaluation of some programming languages in terms of their appropriateness for use as the base for an intelligent robot programming language is presented. This leads to the conclusion that no current language forms an adequate base for intelligent robot programming languages. What is needed as a base is a language for use in the artificial intelligence domain, that incorporates real-time facilities.

The Relevance of AI Research to CAI

1978 ◽  
Vol 6 (3) ◽  
pp. 229-250 ◽  
Author(s):  
Greg P. Kearsley
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Programming Languages ◽  
Rule Induction ◽  
Computer Assisted Instruction ◽  
Current Work ◽  
Computer Assisted ◽  
Language Understanding ◽  
General Theme ◽  
Assisted Instruction

This article provides a tutorial introduction to Artificial Intelligence (AI) research for those involved in Computer Assisted Instruction (CAI). The general theme espoused is that much of the current work in AI, particularly in the areas of natural language understanding systems, rule induction, programming languages, and socratic systems, has important applications to CAI. It is hoped that this tutorial will stimulate or catalyze more intensive interaction between AI and CAI.

scholarly journals Implementation of PI and MPC-Based Speed Controllers for a Drive with Elastic Coupling on a PLC Controller

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3139
Author(s):  
Piotr Serkies ◽  
Adam Gorla
Keyword(s):  
Programming Languages ◽  
Pi Controller ◽  
Elastic Coupling ◽  
Control Structures ◽  
Drive Control ◽  
Advanced Control ◽  
Predictive Controller ◽  
Compact Design ◽  
Signal Processors ◽  
Additional Feedback

This paper presents some of the issues related to the implementation of advanced control structures (PI controller with additional feedback, Model Predictive Controller) for drives with elastic coupling on a programmable logic controller (PLC). The predominant solutions to electric drive control include the use of rapid prototyping cards, signal processors or programmable matrices. Originally, PLC controllers were used to automate sequential processes, but for several years now, a trend related to their implementation for advanced control objects can be observed. This is mainly due to their compact design, immunity to disturbances and standard programming languages. The following chapters of the paper present the mathematical model of the drive and describe the implementation of the proposed control structures. A PI controller with additional feedback loops and a predictive controller are taken into consideration. Their impact on the CPU load was analysed, and the work was summarised by a comprehensive experimental study. The presented results confirm that it is possible to implement advanced control structures on a PLC controller for drives with elastic coupling while maintaining a sufficiently low load on its CPU.

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