RLL-1: A Representation Language Language

Abstract : The field of AI is strewn with knowledge representation languages. The language designer typically designs that language with one particular application domain in mind; as subsequent types of applications are tried, what had originally been useful features are found to be undesirable limitations, and the language is overhauled or scrapped. One remedy to this bleak cycle might be to construct a representation language whose domain is the field of representational languages itself. Toward this end, we designed and implemented RLL-1, a frame-based Representation Language Language. The components of representation languages in general (such as slots and inheritance mechanisms) and of RLL-1 itself, in particular, are encoded declaratively as frames. By modifying these frames, the user can change the semantics of RLL-1's components, and significantly alter the overall character of the RLL-1 environment. Often a large Artificial Intelligence project begins by designing and implementing a high-level language in which to easily and precisely specify the nuances of the task. The language designer typically builds his Representation Language around the one particular highlighted application (such as molecular biology for Units (Stefik), or natural language understanding for KRL (Bobrow & Winograd) and OWL (Szolovits, et al.)). For this reason, his language is often inadequate for any subsequent applications, except those which can be cast in a form similar in structure to the initial task. What had originally been useful features are subsequently found to be undesirable limitations. Consider Units' explicit copying of inherited facts or KRL's sophisticated but slow matcher.

[1]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.

[2]  David E. Smith,et al.  A Frame-Based Production System Architecture , 1980, AAAI.

[3]  Nelleke Aiello,et al.  AGE (Attempt to Generalize): A Knowledge-Based Program for Building Knowledge-Based Programs , 1979, IJCAI.

[4]  Peter Szolovits,et al.  An Overview of OWL, a language for knowledge representation , 1977 .

[5]  Mark Stefik,et al.  An Examination of a Frame-Structured Representation System , 1979, IJCAI.

[6]  Douglas B. Lenat,et al.  Less Than General Production System Architectures , 1977, IJCAI.

[7]  Victor R. Lesser,et al.  A Retrospective View of the Hearsay-II Architecture , 1977, IJCAI.

[8]  Jon Doyle,et al.  A model for deliberation, action, and introspection , 1981, SGAR.

[9]  John P. McDermott,et al.  OPS, A Domain-Independent Production System Language , 1977, IJCAI.

[10]  Terry Winograd,et al.  Beyond programming languages , 1979, CACM.

[11]  Elaine Kant,et al.  Results in Knowledge-Based Program Synthesis , 1979, IJCAI.

[12]  William A. Woods,et al.  What's in a Link: Foundations for Semantic Networks , 1975 .

[13]  Richard W. Weyhrauch,et al.  Prolegomena to a theory of formal reasoning , 1978 .

[14]  Ronald J. Brachman,et al.  ON THE EPISTEMOLOGICAL STATUS OF SEMANTIC NETWORKS , 1979 .

[15]  Jon Doyle,et al.  AMORD explicit control of reasoning , 1977, SIGART Newsl..

[16]  W. W. Bledsoe,et al.  Non-Resolution Theorem Proving , 1977, Artif. Intell..

[17]  Zohar Manna,et al.  A Deductive Approach to Program Synthesis , 1979, TOPL.

[18]  Carl Hewitt,et al.  Description and Theoretical Analysis (Using Schemata) of Planner: A Language for Proving Theorems and Manipulating Models in a Robot , 1972 .

[19]  Douglas B. Lenat,et al.  Designing a rule system that searches for scientific discoveries , 1977, SGAR.

[20]  Scott E. Fahlman,et al.  NETL: A System for Representing and Using Real-World Knowledge , 1979, CL.

[21]  Erik Sandewall,et al.  Ideas About Management Of LISP Data Bases , 1975, IJCAI.

[22]  Victor R. Lesser,et al.  A Multi-Level Organization For Problem Solving Using Many, Diverse, Cooperating Sources Of Knowledge , 1975, IJCAI.

[23]  Ronald J. Brachman,et al.  What's in a Concept: Structural Foundations for Semantic Networks , 1977, Int. J. Man Mach. Stud..

[24]  Raymond Reiter,et al.  On Reasoning by Default , 1978, TINLAP.

[25]  William James Van Melle,et al.  A domain-independent system that aids in constructing knowledge-based consultation programs , 1980 .

[26]  Donald A. Waterman,et al.  Pattern-Directed Inference Systems , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Charles Lanny Forgy,et al.  On the efficient implementation of production systems. , 1979 .

[28]  Lawrence M. Fagan.  VM, representing time-dependent relations in a medical setting , 1980 .

[29]  Douglas B. Lenat,et al.  DESIGNING A RULE SYSTEM THAT SEARCHES FOR SCIENTIFIC DISCOVERIES1 , 1978 .

[30]  Daniel G. Bobrow,et al.  On Overview of KRL, a Knowledge Representation Language , 1976, Cogn. Sci..

[31]  Casimir A. Kulikowski,et al.  EXPERT: A System for Developing Consultation Models , 1979, IJCAI.