China
Africa
Explore chapters and articles related to this topic
Introduction
Published in C.S. Krishnamoorthy, S. Rajeev, Artificial Intelligence and Expert Systems for Artificial Intelligence Engineers, 2018
C.S. Krishnamoorthy, S. Rajeev
Though the works of Simon et al and Shanon demonstrated the concept of intelligent computer programs, the year 1956 is considered to be the start of the topic Artificial Intelligence. This is because the first AI conference, organised by John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shanon at Dartmouth College in New Hampshire, was in 1956. This conference was the first organised effort in the field of machine intelligence. It was at that conference that John McCarthy, the developer of LISP programming language, proposed the term Artificial Intelligence. The Dartmouth conference paved the way for examining the use of computers to process symbols, the need for new languages and the role of computers for theorem proving instead of focusing on hardware that simulated intelligence.
Game-engine based design system for mass customization
Published in Fernando Moreira da Silva, Helena Bártolo, Paulo Bártolo, Rita Almendra, Filipa Roseta, Henrique Amorim Almeida, Ana Cristina Lemos, Challenges for Technology Innovation: An Agenda for the Future, 2017
E. Castro e Costa, J.P. Duarte
A second prototype was written in Racket, a LISP-based programming language. Racket is considered a powerful and versatile language (Leitão 2014), and benefits from the proliferation of modules that extend Racket beyond its native functionalities. One of them is Rosetta (Lopes and Leitão 2011), a module that enables the generation of geometry into a growing number of CAD applications as back-ends. Presently, Rosetta is able to communicate with AutoCAD, Revit, ArchiCAD, Rhinoceros, Sketchup, and OpenGL. Another interesting aspect of Rosetta is that it accepts a number of programming languages as front-ends. Apart from Racket, its native language in which it is programmed, Rosetta “understands” Python, JavaScript, AutoLISP, and Processing, thus relieving users of learning a new programming language should they already know one of these.
Guardnet: A Distributed and Concurrent Programming Environment for Multi-Agent Systems
Published in Takushi Tanaka, Setsuo Ohsuga, Moonis Ali, Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 2022
Motoyuki Takaai, Hideaki Takeda, Toyoaki Nishida
We developed an agent programming language called KC-Basic which runs on Common-Lisp. In KC-Basic, the message receiving parts of agent programs consist of the following elements; agent registrationregistration of message classes and functions to execute for themthe bodies of the functions
Prediction of Online Students Performance by Means of Genetic Programming
Published in Applied Artificial Intelligence, 2018
Rosa Leonor Ulloa-Cazarez, Cuauhtémoc López-Martín, Alain Abran, Cornelio Yáñez-Márquez
S-expressions are a notation that can be both, source code and data. They can be represented as a parse tree (see Figure 1) more easily to be manipulated (Koza 1998; Sette and Boullart 2001). An s-expression can take many formats such as lists, pairs, symbols, strings, and integers. Lisp uses prefix notation which means that in an s-expression the first element is commonly an operator or function name and the rest of the elements are arguments.