10,099 research outputs found
An engineering approach to automatic programming
An exploratory study of the automatic generation and optimization of symbolic programs using DECOM - a prototypical requirement specification model implemented in pure LISP was undertaken. It was concluded, on the basis of this study, that symbolic processing languages such as LISP can support a style of programming based upon formal transformation and dependent upon the expression of constraints in an object-oriented environment. Such languages can represent all aspects of the software generation process (including heuristic algorithms for effecting parallel search) as dynamic processes since data and program are represented in a uniform format
Slisp: A Flexible Software Toolkit for Hybrid, Embedded and Distributed Applications
We describe Slisp (pronounced âEss-Lispâ), a hybrid LispâC programming toolkit for the development of scriptable and distributed applications. Computationally expensive operations implemented as separate C-coded modules are selectively compiled into a small Xlisp interpreter, then called as Lisp functions in a Lisp-coded program. The resulting hybrid program may run in several modes: as a stand-alone executable, embedded in a different C program, as a networked server accessed from another Slisp client, or as a
networked server accessed from a C-coded client. Five years of experience with Slisp, as well experience with other scripting languages such as Tcl and Perl, are summarized. These experiences suggest that Slisp will be most useful for mid-sized applications in which the kinds of scripting and embeddability features provided by Tcl and Perl can be extended in an efïŹcient manner to larger applications, while maintaining a
well-deïŹned standard (Common Lisp) for these extensions. In addition, the generality of Lisp makes Lisp a good candidate for an application-level communication language in distributed environments
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Automatic Generation of Cognitive Theories using Genetic Programming
Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming. Our approach evolves from experimental data cognitive theories that explain âthe mental programâ that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories
Ada in AI or AI in Ada. On developing a rationale for integration
The use of Ada as an Artificial Intelligence (AI) language is gaining interest in the NASA Community, i.e., by parties who have a need to deploy Knowledge Based-Systems (KBS) compatible with the use of Ada as the software standard for the Space Station. A fair number of KBS and pseudo-KBS implementations in Ada exist today. Currently, no widely used guidelines exist to compare and evaluate these with one another. The lack of guidelines illustrates a fundamental problem inherent in trying to compare and evaluate implementations of any sort in languages that are procedural or imperative in style, such as Ada, with those in languages that are functional in style, such as Lisp. Discussed are the strengths and weakness of using Ada as an AI language and a preliminary analysis provided of factors needed for the development of criteria for the integration of these two families of languages and the environments in which they are implemented. The intent for developing such criteria is to have a logical rationale that may be used to guide the development of Ada tools and methodology to support KBS requirements, and to identify those AI technology components that may most readily and effectively be deployed in Ada
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A Survey of Parallel Programming Constructs
This paper surveys the types of parallelism found in Functional, Lisp and Object-Oriented languages. In particular, it concentrates on the addition of high level parallel constructs to these types of languages. The traditional area of the automatic extraction of parallelism by a compiler [39] is ignored here in favor of the addition of new constructs, because the long history of such automatic techniques has shown that they are not sufficient to allow the massive parallelism promised from modem computer architectures [26. 58]. The problem then, simply stated, is given that it is now possible for us to build massively parallel machines and given that our current compilers seem incapable of generating sufficient parallelism automatically, what should the language designer do? A reasonable answer seems to be to add constructs to languages that allow the expression of additional parallelism in a natural way. Indeed that is what the designers of the the Functional, Lisp, and Object-Oriented languages described below have attempted to do. The three particular programming formalisms were picked because most of the initial ideas seem to have been generated by the designers of the functional languages and most of the current activity seems to be in the Lisp and Objected-Oriented domains. There is also a great deal of activity in the Logic programming area, but this activity is more in the area of executing the existing constructs in parallel as opposed to adding constructs specifically designed to increase parallelism
Dynamically typed languages
Dynamically typed languages such as Python and Ruby have experienced a rapid grown in popularity in recent times. However, there is much confusion as to what makes these languages interesting relative to statically typed languages, and little knowledge of their rich history. In this chapter I explore the general topic of dynamically typed languages, how they differ from statically typed languages, their history, and their defining features
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