2 resultados para REHABILITATION OF STRUCTURES

em Massachusetts Institute of Technology


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This paper describes ARLO, a representation language loosely modelled after Greiner and Lenant's RLL-1. ARLO is a structure-based representation language for describing structure-based representation languages, including itself. A given representation language is specified in ARLO by a collection of structures describing how its descriptions are interpreted, defaulted, and verified. This high level description is compiles into lisp code and ARLO structures whose interpretation fulfills the specified semantics of the representation. In addition, ARLO itself- as a representation language for expressing and compiling partial and complete language specifications- is described and interpreted in the same manner as the language it describes and implements. This self-description can be extended of modified to expand or alter the expressive power of ARLO's initial configuration. Languages which describe themselves like ARLO- provide powerful mediums for systems which perform automatic self-modification, optimization, debugging, or documentation. AI systems implemented in such a self-descriptive language can reflect on their own capabilities and limitations, applying general learning and problem solving strategies to enlarge or alleviate them.

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A program was written to solve calculus word problems. The program, CARPS (CALculus Rate Problem Solver), is restricted to rate problems. The overall plan of the program is similar to Bobrow's STUDENT, the primary difference being the introduction of "structures" as the internal model in CARPS. Structures are stored internally as trees. Each structure is designed to hold the information gathered about one object. A description of CARPS is given by working through two problems, one in great detail. Also included is a critical analysis of STUDENT.