Maclisp (or MACLISP, sometimes styled MacLisp or MacLISP) is a programming language, a dialect of the language Lisp. It originated at the Massachusetts Institute of Technology's (MIT) Project MAC (from which it derived its prefix) in the late 1960s and was based on Lisp 1.5. Richard Greenblatt was the main developer of the original codebase for the PDP-6; Jon L. White was responsible for its later maintenance and development. The name Maclisp began being used in the early 1970s to distinguish it from other forks of PDP-6 Lisp, notably BBN Lisp.
Maclisp is a descendant of Lisp 1.5. Maclisp departs from Lisp 1.5 by using a value cell to access and store the dynamic values of variables; Lisp 1.5 used a linear search of an association list to determine a variable's value. The Maclisp variable evaluation is faster but has different variable semantics. Maclisp also employed reader macros to make more readable input and output, termed input/output (I/O). Instead of entering (QUOTE A), one could enter 'A to get the same s-expression. Although both implementations put functions on the property list, Maclisp uses different syntax to define functions. Maclisp also has a load-on-demand feature.
Maclisp began on Digital Equipment Corporation PDP-6 and PDP-10 computers running the Incompatible Timesharing System (ITS); later it was ported to all other PDP-10 operating systems, for example, Timesharing / Total Operating System, TOPS-10 and TOPS-20. The original implementation was in assembly language, but a later implementation on Multics used PL/I. Maclisp developed considerably in its lifetime. Major features were added which in other language systems would typically correspond to major release numbers.
Maclisp was used to implement the Macsyma computer algebra system (CAS) or symbolic algebra program. Macsyma's development also drove several features in Maclisp. The SHRDLU blocks-world program was written in Maclisp, and so the language was in widespread use in the artificial intelligence (AI) research community through the early 1980s.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Metaprogramming is a programming technique in which computer programs have the ability to treat other programs as their data. It means that a program can be designed to read, generate, analyze or transform other programs, and even modify itself while running. In some cases, this allows programmers to minimize the number of lines of code to express a solution, in turn reducing development time. It also allows programs a greater flexibility to efficiently handle new situations without recompilation.
In computer programming, the scope of a name binding (an association of a name to an entity, such as a variable) is the part of a program where the name binding is valid; that is, where the name can be used to refer to the entity. In other parts of the program, the name may refer to a different entity (it may have a different binding), or to nothing at all (it may be unbound). Scope helps prevent name collisions by allowing the same name to refer to different objects – as long as the names have separate scopes.
In computer programming, an S-expression (or symbolic expression, abbreviated as sexpr or sexp) is an expression in a like-named notation for nested list (tree-structured) data. S-expressions were invented for and popularized by the programming language Lisp, which uses them for source code as well as data. In the usual parenthesized syntax of Lisp, an S-expression is classically defined as an atom of the form x, or an expression of the form (x . y) where x and y are S-expressions.
Recently, the author proposed a new approach how to take advantage of common floating car data in context of urban traffic monitoring (cf. Neumann, 2009: Efficient queue length detection at traffic signals using probe vehicle data and data fusion, 16th ITS ...
The paper describes a system platform for virtual human agent simulations that is able to coherently manage the shared virtual environment. Our “agent common environment” (ACE) provides built-in commands for perception and for acting, while the ...