Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
New Programming Languages for Artificial Intelligence Research
ACM Computing Surveys (CSUR)
Formalizing Commonsense: Papers by John McCarthy
Formalizing Commonsense: Papers by John McCarthy
AMORD explicit control of reasoning
Proceedings of the 1977 symposium on Artificial intelligence and programming languages
Micro-Planner Reference Manual
Micro-Planner Reference Manual
Truth Maintenance Systems for Problem Solving
Truth Maintenance Systems for Problem Solving
TINLAP '78 Proceedings of the 1978 workshop on Theoretical issues in natural language processing
A deductive model of control of a problem solver
ACM SIGART Bulletin
Some aspects of symbolic integration via predicate logic programming
ACM SIGSAM Bulletin
LISP A: a lisp-like system for incremental computing
AFIPS '68 (Spring) Proceedings of the April 30--May 2, 1968, spring joint computer conference
Procedural embedding of knowledge in planner
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Epistemological problems of artificial intelligence
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
PLANNER: a language for proving theorems in robots
IJCAI'69 Proceedings of the 1st international joint conference on Artificial intelligence
A note on deduction rules with negative premises
IJCAI'75 Proceedings of the 4th international joint conference on Artificial intelligence - Volume 1
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Artificial Intelligence
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This note describes how the notion of nonmonotonic reasoning emerged in Artificial Intelligence from the mid-1960's to 1980. It gives particular attention to the interplay between three kinds of activities: design of high-level programming systems for AI, design of truth-maintenance systems, and the development of nonmonotonic logics. This was not merely a development from logic to implementation; in several cases there was a development from a system design to a corresponding logic. The article concludes with some reflections on the roles and relationships between logicist theory and system design in AI, and in particular in Knowledge Representation.