Human problem solving: The state of the theory in 1970.
Abstract
WHEN the magician pulls the rabbit from the hat, the spectator can respond either with mystification or with curiosity. He can enjoy the surprise and the wonder of the unexplained (and perhaps inexplicable), or he can search for an explanation. Suppose curiosity is his main response—that he adopts a scientist's attitude toward the mystery. What questions should a scientific theory of magic answer? First, it should predict the performance of a magician handling specified tasks—producing a rabbit from a hat, say. It should explain how the production takes place, what processes are used, and what mechanisms perform those processes. It should predict the incidental phenomena that accompany the magic—the magician's patter and his pretty assistant—and the relation of these to the mystification process. It should show how changes in the attendant conditions—both changes "inside" the members of the audience and changes in the feat of magic—alter the magician's behavior. It should explain how specific and general magician's skills are learned, and what the magician "has" when he has learned them.
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Cognitive science has developed task-performing computational models that decompose cognition into functional components.
“Cognitive science has developed computational models that decompose cognition into functional components.”
From Cognitive computational neuroscience (2018) · cites this paper as [4]
Cites
Newell, A. (1972) · Cited by 6,222 · see citing works
Self-citationDuncker, K. (1945) · Psychological Monographs · doi:10.1037/h0093599 · Cited by 2,938 · see citing works
Elements of a theory of human problem solving.
Newell, A., Shaw, J. C., & Simon, H. A. (1958) · Psychological Review · doi:10.1037/h0048495 · Cited by 1,380 · see citing works
Self-citationThe logic theory machine-A complex information processing system
Newell, A., & Simon, H. (1956) · IEEE Transactions on Information Theory · doi:10.1109/tit.1956.1056797 · Cited by 846 · see citing works
Self-citationGPS : a case study in generality and problem solving
Ernst, G. W., & Newell, A. (1969) · Cited by 508 · see citing works
Self-citationThe processes of creative thinking.
Newell, A., Shaw, J. C., & Simon, H. A. (2011) · Atherton Press eBooks · doi:10.1037/13117-003 · Cited by 476 · see citing works
Self-citationHuman acquisition of concepts for sequential patterns.
Simon, H. A., & Kotovsky, K. (1963) · Psychological Review · doi:10.1037/h0043901 · Cited by 414 · see citing works
Self-citationGulliksen, H. O. (1942) · American Journal of Psychiatry · doi:10.1176/ajp.98.5.782 · Cited by 322 · see citing works
Empirical explorations of the logic theory machine
Newell, A., Shaw, J. C., & Simon, H. A. (1957) · doi:10.1145/1455567.1455605 · Cited by 239 · see citing works
Self-citationInformation-processing analysis of perceptual processes in problem solving.
Simon, H. A., & Barenfeld, M. (1969) · Psychological Review · doi:10.1037/h0028154 · Cited by 160 · see citing works
Self-citationProgramming the logic theory machine
Newell, A., & Shaw, J. C. (1957) · doi:10.1145/1455567.1455606 · Cited by 132 · see citing works
Self-citationA chess mating combinations program
Baylor, G. W., & Simon, H. A. (1966) · doi:10.1145/1464182.1464233 · Cited by 39 · see citing works
Self-citationAN INFORMATION‐PROCESSING EXPLANATION OF SOME PERCEPTUAL PHENOMENA*
Simon, H. A. (1967) · British Journal of Psychology · doi:10.1111/j.2044-8295.1967.tb01051.x · Cited by 34 · see citing works
Self-citationTHE DEVELOPMENT OF SERIAL COMPLETION STRATEGIES: AN INFORMATION PROCESSING ANALYSIS
Klahr, D., & Wallace, J. G. (1970) · British Journal of Psychology · doi:10.1111/j.2044-8295.1970.tb01241.x · Cited by 32 · see citing works
Studies in problem solving ; subject 3 on the crypt-arithmetic task Donald + Gerald = Robert
Newell, A. (2018) · KiltHub Repository · doi:10.1184/r1/6609998 · Cited by 19 · see citing works
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Cognitive computational neuroscience
Kriegeskorte, N., & Douglas, P. K. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0210-5 · Cited by 535 · see citing works
The role of analogy in transfer between similar problem states
Reed, S. K., Ernst, G. W., & Banerji, R. (1974) · Cognitive Psychology · doi:10.1016/0010-0285(74)90020-6 · Cited by 400 · see citing works
Clinical Implications and Challenges of Artificial Intelligence and Deep Learning
Stead, W. W. (2018) · JAMA · doi:10.1001/jama.2018.11029 · Cited by 250 · see citing works
Marcus, N., Cooper, M., & Sweller, J. (1996) · Journal of Educational Psychology · doi:10.1037/0022-0663.88.1.49 · Cited by 244 · see citing works
The intertwined histories of artificial intelligence and education
Doroudi, S. (2023) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-022-00313-2 · Cited by 129 · see citing works
Faith and Fate: Limits of Transformers on Compositionality
Dziri, N., Lu, X., Sclar, M., Li, X. (., Jiang, L., Lin, B. Y., Welleck, S., West, P., Bhagavatula, C., Bras, R. L., et al. (2023) · Advances in Neural Information Processing Systems 36 · doi:10.52202/075280-3081 · Cited by 124 · see citing works
“Applying step-by-step reasoning is fundamental to human intelligence [51, 50].”
BackgroundFaith and Fate: Limits of Transformers on Compositionality
Dziri, N., Lu, X., Sclar, M., Li, X. L., Jiang, L., Lin, B. Y., West, P., Bhagavatula, C., Bras, R. L., Hwang, J. D., et al. (2023) · arXiv · Cited by 124 · see citing works
Raković, M., Winne, P. H., Marzouk, Z., & Chang, D. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12531 · Cited by 26 · see citing works
Zambak, V. S., & Magiera, M. T. (2020) · International Journal of Mathematical Education in Science and Technology · doi:10.1080/0020739x.2020.1762938 · Cited by 14 · see citing works
Eppler, M. J., & Mengis, J. (2004) · The Information Society · doi:10.1080/01972240490507974 · Cited by 44 · see citing works
Coelho Mollo, D., & Millière, R. (2026) · Philosophy and the Mind Sciences · doi:10.33735/phimisci.2026.12307 · Cited by 48 · see citing works
HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models
He, Y., Wu, Y., Jia, Y., Mihalcea, R., Chen, Y., & Deng, N. (2023) · arXiv · doi:10.48550/arxiv.2310.16755 · Cited by 1 · see citing works
- Authors
- Simon, H. A., & Newell, A.
- Affiliations
- Carnegie Mellon University (US)
- Venue
- American Psychologist
- Published
- 1971-02
- Volume
- 26
- Issue
- 2
- Pages
- 145-159
- ISSN
- 0003-066X (ISSN-L)
- 1935-990X
- OpenAlex
- W2078451758
- Cited by
- 635
- References
- 15
- Citations by year
- 2026: 39 · 2025: 58 · 2024: 40 · 2023: 48 · 2022: 38 · 2021: 46 · 2020: 30 · 2019: 37 · 2018: 28 · 2017: 27 · 2016: 18 · 2015: 18 · 2014: 24 · 2013: 13 · 2012: 9
- FWCI
- 40.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Psychologist (publishedVersion)
- Topics
- Social Sciences › Psychology › General Psychology › Academic and Historical Perspectives in Psychology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Keywords
- human problem solving, magic, mystification, prediction
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