Problem Solving
Relational production systems
A relational production system (rps) is a general purpose, formal information processing model developed to support research in artificial intelligence and related areas where a conjunction of predicate calculus literals is a convenient state description language. Rps maintains a strong analogy with type O string grammars. It consists of a “situation”, which is a conjunction of literals, and an unordered set of “relational productions”, analogous to type O string productions. These productions cause the replacement of a subset of literals in the situation by other literals, just as type O string productions cause the replacement of substrings by other substrings. Predictably, this system resembles the more empirical, existing knowledge representation systems, particularly STRIPS, while maintaining a mathematical precision and simplicity which allows proof of useful results.
An overview of KRL, a knowledge representation language
This paper describes krl, a Knowledge Representation Language designed for use in understander systems. It outlines both the general concepts which underlie our research and the details of KRL-0, an experimental implementation of some of these concepts. These forms provide a variety of ways to express the logical structure of the knowledge, in order to give flexibility in associating procedures (for memory and reasoning) with specific pieces of knowledge, and to control the relative accessibility of different facts and descriptions. The formalism for declarative knowledge is based on structured conceptual objects with associated descriptions. These objects form a network of memory units with several different sorts of linkages, each having well-specified implications for the retrieval process.
Scripts, Plans, Goals, and Understanding: An Inquiry into Human Knowledge Structures
Book-length version of the central ideas presented in Roger C. Schank and Robert P. Abelson, "SCRIPTS, PLANS, AND KNOWLEDGE" http://oak.conncoll.edu/parker/com316/progassign/scripts.pdf Hillsdale, NJ: Lawrence Erlbaum Associates
A Network-based knowledge representation and its natural deduction system
Proc. IJCAI 77 VOL 1 MASSACHUSETTS INSTITUTE OF TECHNOLOGY CAMBRIDGE, MASSACHUSETTS, USA AUGUST 22 - 25 , 1977, pp.235-246.
The Art of Artificial Intelligence: Themes and Case Studies of Knowledge Engineering
See also: Stanford Heuristic Programming Project Memo HPP-77-25Proc. IJCAI-77: Fifth International Joint Conference on Artificial Intelligence, pp 1014-1029
Generating project networks
Proc. Fifth Intl. Joint Conference on Artificial Intelligence (IJCAI-77) pp. 888-893, Boston, Mass. USA, August 1977. Reprinted in "Readings in Planning", Morgan-Kaufmann, 1990.
Knowledge structures and language boundaries
Proc. IJCAI 77 VOL 1 MASSACHUSETTS INSTITUTE OF TECHNOLOGY CAMBRIDGE, MASSACHUSETTS, USA AUGUST 22 - 25 , 1977, pp. 151-157.
NUDGE, a knowledge-based scheduling program
Goldstein, I. P., Roberts, R. B.
See also: MIT.Proc. IJCAI 77 VOL 1, MASSACHUSETTS INSTITUTE OF TECHNOLOGY, CAMBRIDGE, MASSACHUSETTS, USA, pp.257-263, AUGUST 22-25
In defence of logic
Proc. IJCAI 77 VOL 1 MASSACHUSETTS INSTITUTE OF TECHNOLOGY CAMBRIDGE, MASSACHUSETTS, USA AUGUST 22 - 25 , 1977, pp.559-565.
Meta-level knowledge: Overview and applications
"We define the concept of meta-level Knowledge, and illustrate it by briefly reviewing four examples that have been described in detail elsewhere. The examples include applications of the idea to tasks such as transfer of expertise from a domain expert to a program, and the maintenance and use of large Knowledge bases. We explore common themes that arise from these examples, and examine broader implications of the idea, in particular its impact on the design and construction of large programs."IJCAI 5, 920-927