dc.contributor.author | Sussman, Gerald Jay | |
dc.contributor.author | Steele, Guy L. Jr. | |
dc.contributor.author | Rich, Charles | |
dc.contributor.author | Doyle, Jon | |
dc.contributor.author | de Kleer, Johan | |
dc.date.accessioned | 2008-08-26T15:36:55Z | |
dc.date.available | 2008-08-26T15:36:55Z | |
dc.date.issued | 1977-08 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/41983 | |
dc.description | This research was conducted at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract number N00014-75-C-0643. | en |
dc.description.abstract | We have implemented an interpreter for a rule-based system, AMORD, based on a non-chronological control structure and a system of automatically maintained data-dependencies. The purpose of this paper is tutorial. We wish to illustrate:
(1) The discipline of explicit control and dependencies,
(2) How to use AMORD, and
(3) One way to implement the mechanisms provided by AMORD.
This paper is organized into sections. The first section is a short "reference manual" describing the major features of AMORD. Next, we present some examples which illustrate the style of expression encouraged by AMORD. This style makes control information explicit in a rule-manipulable form, and depends on an understanding of the use of non-chronological justifications for program beliefs as a means for determining the current set of beliefs. The third section is a brief description of the Truth Maintenance System employed by AMORD for maintaining these justifications and program beliefs. The fourth section presents a completely annotated interpreter for AMORD, written in SCHEME. | en |
dc.description.sponsorship | MIT Artificial Intelligence Laboratory
Department of Defense Advanced Research Projects Agency | en |
dc.language.iso | en_US | en |
dc.publisher | MIT Artificial Intelligence Laboratory | en |
dc.relation.ispartofseries | MIT Artificial Intelligence Laboratory Working Papers, WP-151; | |
dc.title | AMORD: A Deductive Procedure System | en |
dc.type | Working Paper | en |