The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
A truth maintenance system
Abstract
Abstract To choose their actions, reasoning programs must be able to make assumptions and subsequently revise their beliefs when discoveries contradict these assumptions. The Truth Maintenance System (TMS) is a problem solver subsystem for performing these functions by recording and maintaining the reasons for program beliefs. Such recorded reasons are useful in constructing explanations of program actions and in guiding the course of action of a problem solver. This paper describes (1) the representations and structure of the tms , (2) the mechanisms used to revise the current set of beliefs, (3) how dependency-directed backtracking changes the current set of assumptions, (4) techniques for summarizing explanations of beliefs, (5) how to organize problem solvers into “dialectically arguing” modules, (6) how to revise models of the belief systems of others, and (7) methods for embedding control structures in patterns of assumptions. We stress the need of problem solvers to choose between alternative systems of beliefs, and outline a mechanism by which a problem solver can employ rules guiding choices of what to believe, what to want, and what to do.
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Citations
Cites
A FRAMEWORK FOR REPRESENTING KNOWLEDGE
Minsky, M. (1988) · Readings in Cognitive Science · doi:10.1016/b978-1-4832-1446-7.50018-2 · Cited by 4,536
van Orman Quine, W. (1976) · Can Theories be Refuted? · doi:10.1007/978-94-010-1863-0_2 · Cited by 2,709
Fuzzy logic and approximate reasoning: In memory of Grigore Moisil
Zadeh, L. A. (1975) · Synthese · doi:10.1007/bf00485052 · Cited by 1,617
Hintikka, J. (1962) · Cited by 1,536
McDermott, D., & Doyle, J. (1980) · Artificial Intelligence · doi:10.1016/0004-3702(80)90012-0 · Cited by 904
Self-citationComputer Models of Thought and Language
Huesmann, L. R., Schank, R. C., & Colby, K. M. (1974) · The American Journal of Psychology · doi:10.2307/1421990 · Cited by 713
Stallman, R. M., & Sussman, G. J. (1977) · Artificial Intelligence · doi:10.1016/0004-3702(77)90029-7 · Cited by 712
Quine, W. V. O., & Ullian, J. S. (1970) · Medical Entomology and Zoology · Cited by 636
List processing in real time on a serial computer
Baker, H. G. (1978) · Communications of the ACM · doi:10.1145/359460.359470 · Cited by 592
A Framework for Representing Knowledge
Minsky, M. (1997) · The MIT Press eBooks · doi:10.7551/mitpress/4626.003.0005 · Cited by 536
NETL: A System for Representing and Using Real-World Knowledge
Fahlman, S. E. (1979) · OLAC - Open Language Archives Community · Cited by 522
REASONING ABOUT KNOWLEDGE AND ACTION
Moore, R. C. (1981) · Readings in Artificial Intelligence · doi:10.1016/b978-0-934613-03-3.50037-4 · Cited by 367
The Problem of Counterfactual Conditionals.
McKinsey, J. C. C., & Goodman, N. (1947) · Journal of Symbolic Logic · doi:10.2307/2266497 · Cited by 272
Minsky, M. (1980) · Cognitive Science · doi:10.1207/s15516709cog0402_1 · Cited by 209
McDermott, D. (1978) · Cognitive Science · doi:10.1016/s0364-0213(78)80001-9 · Cited by 194
Artificial Intelligence Programming
Eugene Charniak, D., Riesbeck, C. K., McDermott, D., & Meehan, J. R. (2014) · Psychology Press eBooks · doi:10.4324/9781315802251 · Cited by 181
Bastable, P. K. (1968) · Philosophical Studies · doi:10.5840/philstudies19681706 · Cited by 177
On knowing what to say: planning speech acts.
Cohen, P. R. (1978) · PhilPapers (PhilPapers Foundation) · Cited by 174
Reiter, R. (1978) · Theoretical Issues In Natural Language Processing · doi:10.3115/980262.980297 · Cited by 156
Causal and Teleological Reasoning In Circuit Recognition
de Kleer, J. (1979) · Defense Technical Information Center (DTIC) · Cited by 143
Artificial intelligence programming
London, P. E. (1980) · Artificial Intelligence · doi:10.1016/0004-3702(80)90024-7 · Cited by 141
Katz, S. M., & Manna, Z. (1976) · Communications of the ACM · doi:10.1145/360032.360048 · Cited by 136
Heuristic techniques in computer-aided circuit analysis
Sussman, G. J., & Stallman, R. M. (1975) · IEEE Transactions on Circuits and Systems · doi:10.1109/tcs.1975.1083985 · Cited by 122
Truth maintenance systems for problem solving
Doyle, J. (1977) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 121
Self-citationSussman, G. J., & McDermott, D. (1972) · AFIPS Fall Joint Computer Conference (FJCC) · doi:10.1145/1480083.1480156 · Cited by 118
Propagation of constraints applied to circuit synthesis
de Kleer, J., & Sussman, G. J. (1980) · International Journal of Circuit Theory and Applications · doi:10.1002/cta.4490080206 · Cited by 115
The Frame Problem and Related Problems in Artificial Intelligence
Hayes, P. J. (1981) · Elsevier eBooks · doi:10.1016/b978-0-934613-03-3.50020-9 · Cited by 112
Structural complexity of proofs
Statman, R. (1974) · University Microfilms International eBooks · Cited by 74
Loehlin, J. C. (1974) · Artificial Intelligence · doi:10.1016/0004-3702(74)90004-6 · Cited by 73
A Human Oriented Logic for Automatic Theorem-Proving
Nevins, A. J. (1974) · Journal of the ACM · doi:10.1145/321850.321858 · Cited by 69
Chess as problem solving: the development of a tactics analyzer.
Berliner, H. (1975) · Cited by 61
A Three Valued Truth Maintenance System.
McAllester, D. (1978) · Defense Technical Information Center (DTIC) · Cited by 60
A representation for robot plans
Hayes, P. J. (1975) · International Joint Conference on Artificial Intelligence · Cited by 53
de Kleer, J., Doyle, J., Steele, G. L., & Sussman, G. J. (1977) · Defense Technical Information Center (DTIC) · Cited by 53
Self-citationProlegomena to a Theory of Formal Reasoning
Weyhrauch, R. W. (1978) · doi:10.21236/ada065698 · Cited by 50
Dependency Directed Reasoning for Complex Program Understanding
Shrobe, H. E. (1979) · Defense Technical Information Center (DTIC) · Cited by 42
Assimilation of New Information by a Natural Language Understanding System
McDermott, D. (1974) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 41
State deltas: a formalism for representing segments of computation.
Crocker, S. D. (1977) · Cited by 30
Deductive retrieval mechanisms for state description models
Fikes, R. E. (1975) · Defense Technical Information Center (DTIC) · Cited by 28
Reasoning about Knowledge and Action
島田, 俊. (1978) · Medical Entomology and Zoology · Cited by 27
Computer aided evolutionary design for software engineering
Rich, C., & Waters, R. C. (1981) · ACM SIGART Bulletin · doi:10.1145/1056490.1056493 · Cited by 24
(1990) · Knowledge-Based Systems · doi:10.1016/0950-7051(90)90025-d · Cited by 23
Dependency networks as a representation for modelling in general problem solvers.
London, P. E. (1978) · Cited by 21
Very Large Planner-Type Data Bases
McDermott, D. (1975) · Defense Technical Information Center (DTIC) · Cited by 20
Counterfactuals without possible worlds
Turner, R. (1981) · Journal of Philosophical Logic · doi:10.1007/bf00248737 · Cited by 18
The Architecture of Coherent Information System: A General Problem Solving System
Srinivasan (1976) · IEEE Transactions on Computers · doi:10.1109/tc.1976.1674621 · Cited by 18
Network truth-maintenance for deduction and modelling
Thompson, A. M. (1979) · International Joint Conference on Artificial Intelligence · Cited by 17
A note on deduction rules with negative premises
Kramosil, I. (1975) · International Joint Conference on Artificial Intelligence · Cited by 13
A system for incrementally designing and verifying programs.
Moriconi, M. (1977) · Cited by 13
Plan recognition using a hypothesize and revise paradigm: an example
Schmidt, C. F., & Sridharan, N. S. (1977) · International Joint Conference on Artificial Intelligence · Cited by 13
The Use of Equality in Deduction and Knowledge Representation
McAllester, D. (1980) · Cited by 12
A Survey of Contemporary Learning Theories
Suppes, P. (1977) · Springer eBooks · doi:10.1007/978-94-010-1141-9_13 · Cited by 10
Representation of actions that have side-effects
Sridharan, N. S., & Hawrusik, F. (1977) · International Joint Conference on Artificial Intelligence · Cited by 8
The Use of Dependency Relationships in the Control of Reasoning
Doyle, J. (1976) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 8
Self-citationPlausible inference: A multi-valued logic for problem solving
Friedman, L. (1979) · NASA STI Repository (National Aeronautics and Space Administration) · Cited by 7
Research works printed but not linked: 7
- Cox, 1977, Deduction plans: A graphical proof procedure for the first-order predicate calculus, Department of Computer Science, University of Waterloo, Research Report CS-77-28
- De Kleer, 1976, Local methods for localization of failures in electronic circuits, MIT AI Lab, Memo 394
- De Kleer, 1977, MIT AI Lab, Memo 427
- Doyle, 1978, Reflexive interpreters, MIT Department of Electrical Engineering and Computer Science, Ph.D. proposal
- Latombe, 1977, Une application de l'intelligence artificielle a la conception assistée par ordinateur (tropic), Université Scientifique et Médicale de Grenôble, Thesis D.Sc. Mathematiques
- Stansfield, 1978, Integrating truth maintenance systems with propagation of strength of belief as a means of addressing the fusion problem, MIT AI Lab., draft proposal
- Steele, 1978, Constraints, MIT AI Lab., Memo 502
Cited by
(1988) · Cited by 16,582
Maintaining knowledge about temporal intervals
Allen, J. F. (1983) · Communications of the ACM · doi:10.1145/182.358434 · Cited by 7,593
Ginsberg, M. L. (1986) · Artificial Intelligence · doi:10.1016/0004-3702(86)90067-6 · Cited by 218
Generalized subsumption and its applications to induction and redundancy
Buntine, W. (1988) · Artificial Intelligence · doi:10.1016/0004-3702(88)90001-x · Cited by 168
Nobel Turing Challenge: creating the engine for scientific discovery
Kitano, H. (2021) · npj Systems Biology and Applications · doi:10.1038/s41540-021-00189-3 · Cited by 149
Metadata
- Authors
- Doyle, J.
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 1979-11
- Volume
- 12
- Issue
- 3
- Pages
- 231-272
- ISSN
- 0004-3702
- Cited by
- 1,132
- References
- 55
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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