Treffer: Hunting for Paradoxes: A Research Strategy for Cognitive Science.
Title:
Hunting for Paradoxes: A Research Strategy for Cognitive Science.
Authors:
Chater N; Behavioural Science Group, Warwick Business School.
Source:
Topics in cognitive science [Top Cogn Sci] 2025 Jul; Vol. 17 (3), pp. 770-801. Date of Electronic Publication: 2025 Apr 01.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Cognitive Science Society, Inc Country of Publication: United States NLM ID: 101506764 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1756-8765 (Electronic) Linking ISSN: 17568757 NLM ISO Abbreviation: Top Cogn Sci Subsets: MEDLINE
Imprint Name(s):
Original Publication: Hoboken, NJ : Cognitive Science Society, Inc., c2009-
MeSH Terms:
References:
Anderson, J. R. (1990). The adaptive character of thought. Hillsdale, NJ: Lawrence Erlbaum Associates.
Arrow, K. J. (1950). A difficulty in the concept of social welfare. Journal of Political Economy, 58(4), 328–346.
Bacharach, M. (2006). Beyond individual choice: Teams and frames in game theory. Princeton, NJ: Princeton University Press.
Baker, C. L. (1979). Syntactic theory and the projection problem. Linguistic Inquiry, 10, 533–581.
Baker, C. L., & McCarthy, J. J. (1981). The logical problem of language acquisition. Cambridge, MA: MIT Press.
Baronchelli, A., Chater, N., Pastor‐Satorras, R., & Christiansen, M. H. (2012). The biological origin of linguistic diversity. PLoS ONE, 7(10), e48029.
Bovens, L., & Hartmann, S. (2003). Bayesian epistemology. Oxford, England: Oxford University Press.
Braine, M. D. (1978). On the relation between the natural logic of reasoning and standard logic. Psychological Review, 85(1), 1–21.
Brown, J. R. (1991). The laboratory of the mind: Thought experiments in the natural sciences. Abingdon, UK: Routledge.
Brown, R., & Hanlon, C. (1970). Derivational complexity and order of acquisition in child speech. In J. R. Hayes (Ed.) Cognition and the development of language (pp. 11–53). New York: Wiley.
Brown, G., & Walasek, L. (2025). Distinguishing underlying, inferred and expressed preferences, attitudes, and beliefs: An absence of (mental) flatness? Topics in Cognitive Science, 17(3), 681–712. https://doi.org/10.1111/tops.12787.
Chater, N. (2018). The mind is flat. London: Penguin Random House.
Chater, N., & Christiansen, M. H. (2010). Language acquisition meets language evolution. Cognitive Science, 34, 1131–1157.
Chater, N., & Christiansen, M. H. (2022). Grammar through spontaneous order. In S. Lappin & J.‐P. Bernady (Eds.), Algebraic structures in natural language (pp. 65–79). Abingdon, UK: CRC Press.
Chater, N., & Misyak, J. (2021). Spontaneous communicative conventions through virtual bargaining. In S. Muggleton & N. Chater (Eds.), Human‐like machine intelligence (pp. 52–67). Oxford, England: Oxford University Press.
Chater, N., Reali, F., & Christiansen, M. H. (2009). Restrictions on biological adaptation in language evolution. Proceedings of the National Academy of Sciences, 106, 1015–1020.
Chater, N., Tenenbaum, J., & Yuille, A. (Eds.) (2006). Special issue on probabilistic models of cognition. Trends in Cognitive Sciences, 10(7), 287–344.
Chater, N., & Vitányi, P. (2007). ‘Ideal learning’ of natural language: Positive results about learning from positive evidence. Journal of Mathematical Psychology, 51, 135–163.
Chater, N., & Vlaev, I. (2011). The instability of value. In M. Delgado, E. A. Phelps, & T. W. Robbins (Eds.), Decision making: Attention and performance XXIII (pp. 81–100). Oxford, England: Oxford University Press.
Chater, N., Zeitoun, H., & Melkonyan, T. (2022). The paradox of social interaction: Shared intentionality, we‐reasoning, and virtual bargaining, Psychological Review, 129(3), 415–437.
Chater, N., Zhu, J. Q., Spicer, J., Sundh, J., León‐Villagrá, P., & Sanborn, A. (2020). Probabilistic biases meet the Bayesian brain. Current Directions in Psychological Science, 29(5), 506–512.
Christiansen, M. H. (1992). The (non) necessity of recursion in natural language processing. In J. D. Laird, P. J. Langley, & R. M. Young (Eds.), Proceedings of the 14th annual conference of the cognitive science society (pp. 665–670). Mahwah, NJ: Erlbaum.
Christiansen, M. H., & Chater, N. (2008). Language as shaped by the brain. Behavioral and Brain Sciences, 31, 489–558.
Christiansen, M. H., & Chater, N. (2016). Creating language: Integrating evolution, acquisition, and processing. Cambridge, MA: MIT Press.
Christiansen, M. H., & Chater, N. (2022). The language game: How improvisation created language and changed the world. New York, NY: Basic Books.
Chomsky, N. (1980). Rules and representations. New York, NY: Columbia University Press.
Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36(3), 181–204.
Clark, H. H. (1996). Using language. Cambridge, UK: Cambridge University Press.
Contreras Kallens, P., & Christiansen, M. H. (2025). Distributional semantics: Meaning through culture and interaction. Topics in Cognitive Science, 17(3), 739–769. https://doi.org/10.1111/tops.12771.
Contreras Kallens, P., Kristensen‐McLachlan, R. D., & Christiansen, M. H. (2023). Large language models demonstrate the potential of statistical learning in language. Cognitive Science, 47(3), e13256.
Crain, S., & Lillo‐Martin, D. (1999). An introduction to linguistic theory and language acquisition. Oxford, England: Wiley‐Blackwell.
Crawford, V. P., Costa‐Gomes, M. A., & Iriberri, N. (2013). Structural models of nonequilibrium strategic thinking: Theory, evidence, and applications. Journal of Economic Literature, 51(1), 5–62.
Crupi, V., Chater, N., & Tentori, K. (2013). New axioms for probability and likelihood ratio measures. British Journal for the Philosophy of Science, 64(1), 189–204.
Dasgupta, I., Schulz, E., & Gershman, S. J. (2017). Where do hypotheses come from? Cognitive Psychology, 96, 1–25.
Dasgupta, I., Schulz, E., Goodman, N. D., & Gershman, S. J. (2018). Remembrance of inferences past: Amortization in human hypothesis generation, Cognition, 178, 67–81.
Doya, K., Ishii, S., Pouget, A., & Rao, R. P. N. (2007). Bayesian brain: Probabilistic approaches to neural coding. Cambridge, MA: MIT Press.
Dretske, F. I. (1981). Knowledge and the flow of information. Cambridge, MA: MIT Press.
Earman, J. (1992). Bayes or bust? A critical examination of Bayesian confirmation theory. Cambridge, MA: MIT Press.
Ellis, K., Wong, L., Nye, M., Sable‐Meyer, M., Cary, L., Anaya Pozo, L., Hewitt, L., Solar‐Lezama, A., & Tenenbaum, J. B. (2023). Dreamcoder: Growing generalizable, interpretable knowledge with wake–sleep Bayesian program learning. Philosophical Transactions of the Royal Society A, 381(2251), 20220050.
Farrell, J., & Rabin, M. (1996). Cheap talk. Journal of Economic Perspectives, 10(3), 103–118.
Foucault, M. (1972). The archaeology of knowledge (A. M. Sheridan Smith, Trans.). Syracuse, NY: Pantheon Books. (Original work published 1969).
Gendler, T. S. (1998). Galileo and the indispensability of scientific thought experiment. British Journal for the Philosophy of Science, 49(3), 397–424.
Gold, E. M. (1967). Language identification in the limit. Information and control, 10(5), 447–474.
Goodman, N. (1955). Fact, fiction and forecast. Cambridge, MA: Harvard University Press.
Goodman, N. D., & Frank, M. C. (2016). Pragmatic language interpretation as probabilistic inference. Trends in Cognitive Sciences, 20(11), 818–829.
Grice, H. P. (1957). Meaning. Philosophical Review, 66(3), 377–388.
Griffiths, T. L., Chater, N., & Tenenbaum, J. B. (2024). Bayesian models of cognition: Reverse engineering the mind. Cambridge MA: MIT Press.
Grzywacz, N. M., & Balboa, R. M. (2002). A Bayesian framework for sensory adaptation. Neural Computation, 14(3), 543–559.
Hahn, U. (2011). The problem of circularity in evidence, argument, and explanation. Perspectives on Psychological Science, 6, 172–182.
Hahn, U., & Oaksford, M. (2007). The rationality of informal argumentation: A Bayesian approach to reasoning fallacies. Psychological Review, 114, 704–732.
Harman, G. H. (1965). The inference to the best explanation. Philosophical Review, 74(1), 88–95.
Harman, G. (1986). Change in view: Principles of reasoning. Cambridge, MA: MIT Press.
Harman, G. (2001). General foundations versus rational insight. Philosophy and Phenomenological Research, 63(3), 657–663.
Heller, M. (1991). The happiest thought of Einstein's life. Astronomy Quarterly, 8(3), 177–180.
Ho, T., Camerer, C. F., & Weigelt, K. (1998). Iterated dominance and iterated best response in experimental “p‐beauty contests.” American Economic Review, 88(4), 947–969.
Hodgetts, C. J., & Hahn, U. (2025). The limited place in cognitive space. Topics in Cognitive Science, 17(3), 662–680. https://doi.org/10.1111/tops.70001.
Hornstein, N., & Lightfoot, D. (1981). Explanation in linguistics: The logical problem of language acquisition. London, UK: Longman.
Howson, C., & Urbach, P. (1989). Scientific reasoning: The Bayesian approach. LaSalle, IL: Open Court.
Hsu, A., Chater, N., & Vitányi, P. (2011). The probabilistic analysis of language acquisition: Theoretical, computational, and experimental analysis. Cognition, 120, 380–390.
Hsu, A., Chater, N., & Vitányi, P. (2013). Language learning from positive evidence, reconsidered: A simplicity‐based approach. Topics in Cognitive Science, 5(1), 35–55. https://doi.org/10.1111/tops.12005.
Inhelder, B., & Piaget, J. (1958). The growth of logical thinking: From childhood to adolescence (A. Parsons & S. Milgram, Trans.). New York, NY: Basic Books.
Knill, D. C., & Richards, W. (1996). Perception as Bayesian Inference. Cambridge, MA: MIT Press.
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago, IL: University of Chicago Press.
Laming, D. R. J. (1997). The measurement of sensation. Oxford, England: Oxford University Press.
Li, M., & Vitányi, P. (2019). An introduction to Kolmogorov complexity and its applications (4th ed.). Berlin: Springer.
Lockhead, G. R. (1992). Psychophysical scaling: Judgments of attributes or objects? Behavioral and Brain Sciences, 15(3), 543–558.
Loomes, G. (2010). Modeling choice and valuation in decision experiments. Psychological Review, 117(3), 902–924.
MacKay, D. J. C. (2003). Information theory, inference and learning algorithms. Cambridge, UK: Cambridge University Press.
McNamara, J. M., & Houston, A. I. (1986). The common currency for behavioral decisions. American Naturalist, 127(3), 358–378.
Manktelow, K. I., & Over, D. E. (1991). Social roles and utilities in reasoning with deontic conditionals. Cognition, 39, 85–105.
McKenzie, C. R., & Nelson, J. D. (2003). What a speaker's choice of frame reveals: Reference points, frame selection, and framing effects. Psychonomic Bulletin and Review, 10(3), 596–602.
Mehta, J., Starmer, C., & Sugden, R. (1994). The nature of salience: An experimental investigation of pure coordination games. American Economic Review, 84(3), 658–673.
Melkonyan, T., Zeitoun, H., & Chater, N. (2018). Collusion in Bertrand versus Cournot competition: A virtual bargaining approach. Management Science, 64(12), 5599–5609.
Melkonyan, T., Zeitoun, H., & Chater, N. (2022). The cognitive foundations of tacit commitments: A virtual bargaining model of dynamic interactions. Journal of Mathematical Psychology, 108, 102640.
Mercier, H., & Sperber, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34(2), 57–74.
Mercier, H., & Sperber, D. (2017). The enigma of reason. Cambridge, MA: Harvard University Press.
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21(6), 1087–1092.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for information processing. Psychological Review, 63, 81–97.
Misyak, J. B., & Chater, N. (2014). Virtual bargaining: A theory of social decision‐making. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1655), 20130487.
Misyak, J. B., & Chater, N. (2022). Instantaneous systems of communicative conventions through virtual bargaining. Cognition, 225, 105097.
Misyak, J. B., Melkonyan, T., Zeitoun, H., & Chater, N. (2014). Unwritten rules: Virtual bargaining underpins social interaction, culture, and society. Trends in Cognitive Sciences, 18(10), 512–519.
Misyak, J. B., Noguchi, T., & Chater, N. (2016). Instantaneous conventions: The emergence of flexible communicative signals. Psychological Science, 27(12), 1550–1561.
Morgan, J. L., Bonamo, K. M., & Travis, L. L. (1995). Negative evidence on negative evidence. Developmental Psychology, 31(2), 180–197.
Nagel, R. (1995). Unraveling in guessing games: An experimental study. American Economic Review, 85(5), 1313–1326.
Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., & Ng, A. Y. (2011). Multimodal deep learning. Proceedings of the 28th International Conference on Machine Learning (ICML‐11), Bellevue, WA (pp. 689–696).
Noguchi, T., & Stewart, N. (2018). Multialternative decision by sampling: A model of decision making constrained by process data. Psychological Review, 125(4), 512–544.
Norton, J. D. (1991). Thought experiments in Einstein's work. In T. Horowitz & G. Massey (Eds.), Thought experiments in science and philosophy (pp. 129–148). Lanham: Rowman & Littlefield.
Oaksford, M. (1988). Cognition and enquiry: The pragmatics of conditional reasoning (Doctoral dissertation). Centre for Cognitive Science, University of Edinburgh.
Oaksford, M. (2025). Social rationality and human reasoning: Expressivism and the flat mind. Topics in Cognitive Science, 17(3), 636–661. https://doi.org/10.1111/tops.12757.
Oaksford, M., & Chater, N. (1994). A rational analysis of the selection task as optimal data selection. Psychological Review, 101, 608–631.
Oaksford, M., & Chater, N. (1998). Rational models of cognition. Oxford, England: Oxford University Press.
Oaksford, M., & Chater, N. (2007). Bayesian rationality: The probabilistic approach to human reasoning. Oxford, England: Oxford University Press.
Oaksford, M., & Chater, N. (2013). Dynamic inference and everyday conditional reasoning in the new paradigm. Thinking and Reasoning, 19, 346–379. https://doi.org/10.1080/13546783.2013.808163.
Oaksford, M., & Chater, N. (2017). Causal models and conditional reasoning. In M. Waldmann (Ed.), Oxford handbook of causal reasoning (pp. 327–346). Oxford, England: Oxford University Press.
Oaksford, M., Chater, N., & Larkin, J. (2000). Probabilities and polarity biases in conditional inference. Journal of Experimental Psychology: Learning, Memory & Cognition, 26, 883–899.
Oaksford, M., & Hall, S. (2016). On the source of human irrationality. Trends in Cognitive Sciences, 20, 336–344.
Osherson, D. N., Stob, M., & Weinstein, S. (1985). Systems that learn: An introduction to learning theory for cognitive and computer scientists. Cambridge, MA: MIT Press.
Pearl, J. (1988). Probabilistic reasoning in intelligent systems. San Mateo, CA: Morgan Kaufman.
Pearl, J. (2000). Causality. Cambridge, UK: Cambridge University Press.
Pinker, S. (1989). Learnability and cognition: The acquisition of argument structure. Cambridge, MA: MIT Press.
Pinker, S. (1994). The language instinct: How the mind creates language. New York, NY: William Morrow and Company.
Pinker, S., & Bloom, P. (1990). Natural language and natural selection. Behavioral and Brain Sciences, 13(4), 707–784.
Priest, G., Tanaka, K., & Weber, Z. (2022). Paraconsistent Logic. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2022 ed.). Standford, CA: Stanford University. https://plato.stanford.edu/archives/spr2022/entries/logic‐paraconsistent/.
Rao, R. P., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra‐classical receptive‐field effects. Nature Neuroscience, 2(1), 79–87.
Rawls, J. (1971). A theory of justice. Cambridge, MA: Harvard University Press.
Rips, L. J. (1994). The psychology of proof: Deductive reasoning in human thinking. Cambridge, MA: The MIT Press.
Rumelhart, D. E. (1980). Schemata: The building blocks of cognition. In R. J. Spiro, B. C. Bruce, & W. F. Brewer (Eds.), Theoretical issues in reading comprehension (pp. 33–58). Abingdon, UK: Routledge.
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back‐propagating errors. Nature, 323(6088), 533–536.
Rumelhart, D. E., & McClelland, J. L. L. (1986). On learning the past tenses of English verbs. In D. E. Rumelhart & J. L. McClelland (Eds.), Parallel distributed processing: Explorations in the microstructures of cognition (Vol. 2, pp. 216–271). Cambridge, MA: MIT Press.
Rumelhart, D. E., & McClelland, J. L. & the PDP Research Group. (1986) Parallel distributed processing: Explorations in the microstructures of cognition (2 volumes). Cambridge, MA: MIT Press.
Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. (1986). Sequential thought processes in PDP models. In D. E. Rumelhart & J. L. McClelland (Eds.), Parallel distributed processing: Explorations in the microstructures of cognition (Vol. 2, pp. 3–57). Cambridge, MA: MIT Press.
Sanborn, A. N., & Chater, N. (2016). Bayesian brains without probabilities. Trends in Cognitive Sciences, 20(12), 883–893.
Schelling, T. C. (1960). The strategy of conflict. Cambridge, MA: Harvard University Press.
Scholten, M., & Read, D. (2010). The psychology of intertemporal tradeoffs. Psychological Review, 117(3), 925–944.
Shafto, P., Goodman, N. D., & Griffiths, T. L. (2014). A rational account of pedagogical reasoning: Teaching by, and learning from, examples. Cognitive Psychology, 71, 55–89.
Sedgewick, R., & Wayne, K. (2022). Algorithms (4th ed.). Cambridge, MA: MIT Press.
Sen, A. K. (1977). Rational fools: A critique of the behavioral foundations of economic theory. Philosophy and Public Affairs, 6(4), 317–344.
Sengupta, P., & Garrity, P. (2013). Sensing temperature. Current Biology, 23(8), R304–R307.
Sher, S., & McKenzie, C. R. (2006). Information leakage from logically equivalent frames. Cognition, 101(3), 467–494.
Skinner, B. F. (1957). Verbal behavior. Norwalk, CT: Appleton‐Century‐Crofts.
Sloman, S., Rottenstreich, Y., Wisniewski, E., Hadjichristidis, C., & Fox, C. R. (2004). Typical versus atypical unpacking and superadditive probability judgment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(3), 573–582.
Solomonoff, R. J. (1978). Complexity‐based induction systems: Comparisons and convergence theorems. IEEE Transactions on Information Theory, IT24, 422–432.
Sperber, D., Cara, F., & Girotto, V. (1995). Relevance theory explains the selection task. Cognition, 57(1), 31–95.
Stewart, N. (2009). EPS prize lecture: Decision by sampling: The role of the decision environment in risky choice. Quarterly Journal of Experimental Psychology, 62(6), 1041–1062.
Stewart, N., Brown, G. D. A., & Chater, N. (2005). Absolute identification by relative judgment. Psychological Review, 112, 881–911.
Stewart, N., Chater, N., & Brown, G. D. A. (2006). Decision by sampling. Cognitive Psychology, 53, 1–26.
Taylor, F. S. (1942). The origin of the thermometer. Annals of Science, 5(2), 129–156.
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331(6022), 1279–1285.
Trujillo Jiménez, D., Zhang, M., Zhi‐Xuan, T., Tenenbaum, J. B., & Levine, S. (2025). Resource rational virtual bargaining for moral judgment: Towards a probabilistic cognitive model. Topics in Cognitive Science, 17(3), 713–738. https://doi.org/10.1111/tops.12781.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.
Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90(4), 293–315.
Vitányi, P. M., & Chater, N. (2017). Identification of probabilities. Journal of Mathematical Psychology, 76, 13–24.
Vul, E., Goodman, N.D., Griffiths, T. L., & Tenenbaum, J. B. (2014). One and done? Optimal decisions from very few samples. Cognitive Science, 38(4), 599–637.
Walasek, L., & Brown, G. D. (2023). Incomparability and incommensurability in choice: No common currency of value? Perspectives on Psychological Science, 19(6), 1011–1030. https://doi.org/10.1177/17456916231192828.
Yang, Y., & Piantadosi, S. T. (2022). A model for learning strings is not a model of language. Proceedings of the National Academy of Sciences, 119(12), e2201651119.
Zeitoun, H., Melkonyan, T., & Chater, N. (2023). The social contract in miniature: How virtual bargaining supports team production. Academy of Management Review, 48(3), 432–462.
Zhu, J. ‐Q., Sanborn, A., & Chater, N. (2020). The Bayesian sampler: Generic Bayesian inference causes incoherence in human probability judgments. Psychological Review, 127(5), 719–748.
Zhu, J. ‐Q., Sundh, J., Spicer, J., Chater, N., & Sanborn, A. N. (2024). The autocorrelated Bayesian sampler: A rational process for probability judgments, estimates, confidence intervals, choices, confidence judgments, and response times. Psychological Review, 131(2), 456–493.
Zuidema, W. (2002). How the poverty of the stimulus solves the poverty of the stimulus. In S. Becker, S. Thrun, & K. Obermayer (Eds.) Advances in Neural Information Processing Systems (Vol. 15, pp. 51–58). MIT Press. https://proceedings.neurips.cc/paper_files/paper/2002/hash/04ad5632029cbfbed8e136e5f6f7ddfa‐Abstract.html.
Arrow, K. J. (1950). A difficulty in the concept of social welfare. Journal of Political Economy, 58(4), 328–346.
Bacharach, M. (2006). Beyond individual choice: Teams and frames in game theory. Princeton, NJ: Princeton University Press.
Baker, C. L. (1979). Syntactic theory and the projection problem. Linguistic Inquiry, 10, 533–581.
Baker, C. L., & McCarthy, J. J. (1981). The logical problem of language acquisition. Cambridge, MA: MIT Press.
Baronchelli, A., Chater, N., Pastor‐Satorras, R., & Christiansen, M. H. (2012). The biological origin of linguistic diversity. PLoS ONE, 7(10), e48029.
Bovens, L., & Hartmann, S. (2003). Bayesian epistemology. Oxford, England: Oxford University Press.
Braine, M. D. (1978). On the relation between the natural logic of reasoning and standard logic. Psychological Review, 85(1), 1–21.
Brown, J. R. (1991). The laboratory of the mind: Thought experiments in the natural sciences. Abingdon, UK: Routledge.
Brown, R., & Hanlon, C. (1970). Derivational complexity and order of acquisition in child speech. In J. R. Hayes (Ed.) Cognition and the development of language (pp. 11–53). New York: Wiley.
Brown, G., & Walasek, L. (2025). Distinguishing underlying, inferred and expressed preferences, attitudes, and beliefs: An absence of (mental) flatness? Topics in Cognitive Science, 17(3), 681–712. https://doi.org/10.1111/tops.12787.
Chater, N. (2018). The mind is flat. London: Penguin Random House.
Chater, N., & Christiansen, M. H. (2010). Language acquisition meets language evolution. Cognitive Science, 34, 1131–1157.
Chater, N., & Christiansen, M. H. (2022). Grammar through spontaneous order. In S. Lappin & J.‐P. Bernady (Eds.), Algebraic structures in natural language (pp. 65–79). Abingdon, UK: CRC Press.
Chater, N., & Misyak, J. (2021). Spontaneous communicative conventions through virtual bargaining. In S. Muggleton & N. Chater (Eds.), Human‐like machine intelligence (pp. 52–67). Oxford, England: Oxford University Press.
Chater, N., Reali, F., & Christiansen, M. H. (2009). Restrictions on biological adaptation in language evolution. Proceedings of the National Academy of Sciences, 106, 1015–1020.
Chater, N., Tenenbaum, J., & Yuille, A. (Eds.) (2006). Special issue on probabilistic models of cognition. Trends in Cognitive Sciences, 10(7), 287–344.
Chater, N., & Vitányi, P. (2007). ‘Ideal learning’ of natural language: Positive results about learning from positive evidence. Journal of Mathematical Psychology, 51, 135–163.
Chater, N., & Vlaev, I. (2011). The instability of value. In M. Delgado, E. A. Phelps, & T. W. Robbins (Eds.), Decision making: Attention and performance XXIII (pp. 81–100). Oxford, England: Oxford University Press.
Chater, N., Zeitoun, H., & Melkonyan, T. (2022). The paradox of social interaction: Shared intentionality, we‐reasoning, and virtual bargaining, Psychological Review, 129(3), 415–437.
Chater, N., Zhu, J. Q., Spicer, J., Sundh, J., León‐Villagrá, P., & Sanborn, A. (2020). Probabilistic biases meet the Bayesian brain. Current Directions in Psychological Science, 29(5), 506–512.
Christiansen, M. H. (1992). The (non) necessity of recursion in natural language processing. In J. D. Laird, P. J. Langley, & R. M. Young (Eds.), Proceedings of the 14th annual conference of the cognitive science society (pp. 665–670). Mahwah, NJ: Erlbaum.
Christiansen, M. H., & Chater, N. (2008). Language as shaped by the brain. Behavioral and Brain Sciences, 31, 489–558.
Christiansen, M. H., & Chater, N. (2016). Creating language: Integrating evolution, acquisition, and processing. Cambridge, MA: MIT Press.
Christiansen, M. H., & Chater, N. (2022). The language game: How improvisation created language and changed the world. New York, NY: Basic Books.
Chomsky, N. (1980). Rules and representations. New York, NY: Columbia University Press.
Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36(3), 181–204.
Clark, H. H. (1996). Using language. Cambridge, UK: Cambridge University Press.
Contreras Kallens, P., & Christiansen, M. H. (2025). Distributional semantics: Meaning through culture and interaction. Topics in Cognitive Science, 17(3), 739–769. https://doi.org/10.1111/tops.12771.
Contreras Kallens, P., Kristensen‐McLachlan, R. D., & Christiansen, M. H. (2023). Large language models demonstrate the potential of statistical learning in language. Cognitive Science, 47(3), e13256.
Crain, S., & Lillo‐Martin, D. (1999). An introduction to linguistic theory and language acquisition. Oxford, England: Wiley‐Blackwell.
Crawford, V. P., Costa‐Gomes, M. A., & Iriberri, N. (2013). Structural models of nonequilibrium strategic thinking: Theory, evidence, and applications. Journal of Economic Literature, 51(1), 5–62.
Crupi, V., Chater, N., & Tentori, K. (2013). New axioms for probability and likelihood ratio measures. British Journal for the Philosophy of Science, 64(1), 189–204.
Dasgupta, I., Schulz, E., & Gershman, S. J. (2017). Where do hypotheses come from? Cognitive Psychology, 96, 1–25.
Dasgupta, I., Schulz, E., Goodman, N. D., & Gershman, S. J. (2018). Remembrance of inferences past: Amortization in human hypothesis generation, Cognition, 178, 67–81.
Doya, K., Ishii, S., Pouget, A., & Rao, R. P. N. (2007). Bayesian brain: Probabilistic approaches to neural coding. Cambridge, MA: MIT Press.
Dretske, F. I. (1981). Knowledge and the flow of information. Cambridge, MA: MIT Press.
Earman, J. (1992). Bayes or bust? A critical examination of Bayesian confirmation theory. Cambridge, MA: MIT Press.
Ellis, K., Wong, L., Nye, M., Sable‐Meyer, M., Cary, L., Anaya Pozo, L., Hewitt, L., Solar‐Lezama, A., & Tenenbaum, J. B. (2023). Dreamcoder: Growing generalizable, interpretable knowledge with wake–sleep Bayesian program learning. Philosophical Transactions of the Royal Society A, 381(2251), 20220050.
Farrell, J., & Rabin, M. (1996). Cheap talk. Journal of Economic Perspectives, 10(3), 103–118.
Foucault, M. (1972). The archaeology of knowledge (A. M. Sheridan Smith, Trans.). Syracuse, NY: Pantheon Books. (Original work published 1969).
Gendler, T. S. (1998). Galileo and the indispensability of scientific thought experiment. British Journal for the Philosophy of Science, 49(3), 397–424.
Gold, E. M. (1967). Language identification in the limit. Information and control, 10(5), 447–474.
Goodman, N. (1955). Fact, fiction and forecast. Cambridge, MA: Harvard University Press.
Goodman, N. D., & Frank, M. C. (2016). Pragmatic language interpretation as probabilistic inference. Trends in Cognitive Sciences, 20(11), 818–829.
Grice, H. P. (1957). Meaning. Philosophical Review, 66(3), 377–388.
Griffiths, T. L., Chater, N., & Tenenbaum, J. B. (2024). Bayesian models of cognition: Reverse engineering the mind. Cambridge MA: MIT Press.
Grzywacz, N. M., & Balboa, R. M. (2002). A Bayesian framework for sensory adaptation. Neural Computation, 14(3), 543–559.
Hahn, U. (2011). The problem of circularity in evidence, argument, and explanation. Perspectives on Psychological Science, 6, 172–182.
Hahn, U., & Oaksford, M. (2007). The rationality of informal argumentation: A Bayesian approach to reasoning fallacies. Psychological Review, 114, 704–732.
Harman, G. H. (1965). The inference to the best explanation. Philosophical Review, 74(1), 88–95.
Harman, G. (1986). Change in view: Principles of reasoning. Cambridge, MA: MIT Press.
Harman, G. (2001). General foundations versus rational insight. Philosophy and Phenomenological Research, 63(3), 657–663.
Heller, M. (1991). The happiest thought of Einstein's life. Astronomy Quarterly, 8(3), 177–180.
Ho, T., Camerer, C. F., & Weigelt, K. (1998). Iterated dominance and iterated best response in experimental “p‐beauty contests.” American Economic Review, 88(4), 947–969.
Hodgetts, C. J., & Hahn, U. (2025). The limited place in cognitive space. Topics in Cognitive Science, 17(3), 662–680. https://doi.org/10.1111/tops.70001.
Hornstein, N., & Lightfoot, D. (1981). Explanation in linguistics: The logical problem of language acquisition. London, UK: Longman.
Howson, C., & Urbach, P. (1989). Scientific reasoning: The Bayesian approach. LaSalle, IL: Open Court.
Hsu, A., Chater, N., & Vitányi, P. (2011). The probabilistic analysis of language acquisition: Theoretical, computational, and experimental analysis. Cognition, 120, 380–390.
Hsu, A., Chater, N., & Vitányi, P. (2013). Language learning from positive evidence, reconsidered: A simplicity‐based approach. Topics in Cognitive Science, 5(1), 35–55. https://doi.org/10.1111/tops.12005.
Inhelder, B., & Piaget, J. (1958). The growth of logical thinking: From childhood to adolescence (A. Parsons & S. Milgram, Trans.). New York, NY: Basic Books.
Knill, D. C., & Richards, W. (1996). Perception as Bayesian Inference. Cambridge, MA: MIT Press.
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago, IL: University of Chicago Press.
Laming, D. R. J. (1997). The measurement of sensation. Oxford, England: Oxford University Press.
Li, M., & Vitányi, P. (2019). An introduction to Kolmogorov complexity and its applications (4th ed.). Berlin: Springer.
Lockhead, G. R. (1992). Psychophysical scaling: Judgments of attributes or objects? Behavioral and Brain Sciences, 15(3), 543–558.
Loomes, G. (2010). Modeling choice and valuation in decision experiments. Psychological Review, 117(3), 902–924.
MacKay, D. J. C. (2003). Information theory, inference and learning algorithms. Cambridge, UK: Cambridge University Press.
McNamara, J. M., & Houston, A. I. (1986). The common currency for behavioral decisions. American Naturalist, 127(3), 358–378.
Manktelow, K. I., & Over, D. E. (1991). Social roles and utilities in reasoning with deontic conditionals. Cognition, 39, 85–105.
McKenzie, C. R., & Nelson, J. D. (2003). What a speaker's choice of frame reveals: Reference points, frame selection, and framing effects. Psychonomic Bulletin and Review, 10(3), 596–602.
Mehta, J., Starmer, C., & Sugden, R. (1994). The nature of salience: An experimental investigation of pure coordination games. American Economic Review, 84(3), 658–673.
Melkonyan, T., Zeitoun, H., & Chater, N. (2018). Collusion in Bertrand versus Cournot competition: A virtual bargaining approach. Management Science, 64(12), 5599–5609.
Melkonyan, T., Zeitoun, H., & Chater, N. (2022). The cognitive foundations of tacit commitments: A virtual bargaining model of dynamic interactions. Journal of Mathematical Psychology, 108, 102640.
Mercier, H., & Sperber, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34(2), 57–74.
Mercier, H., & Sperber, D. (2017). The enigma of reason. Cambridge, MA: Harvard University Press.
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21(6), 1087–1092.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for information processing. Psychological Review, 63, 81–97.
Misyak, J. B., & Chater, N. (2014). Virtual bargaining: A theory of social decision‐making. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1655), 20130487.
Misyak, J. B., & Chater, N. (2022). Instantaneous systems of communicative conventions through virtual bargaining. Cognition, 225, 105097.
Misyak, J. B., Melkonyan, T., Zeitoun, H., & Chater, N. (2014). Unwritten rules: Virtual bargaining underpins social interaction, culture, and society. Trends in Cognitive Sciences, 18(10), 512–519.
Misyak, J. B., Noguchi, T., & Chater, N. (2016). Instantaneous conventions: The emergence of flexible communicative signals. Psychological Science, 27(12), 1550–1561.
Morgan, J. L., Bonamo, K. M., & Travis, L. L. (1995). Negative evidence on negative evidence. Developmental Psychology, 31(2), 180–197.
Nagel, R. (1995). Unraveling in guessing games: An experimental study. American Economic Review, 85(5), 1313–1326.
Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., & Ng, A. Y. (2011). Multimodal deep learning. Proceedings of the 28th International Conference on Machine Learning (ICML‐11), Bellevue, WA (pp. 689–696).
Noguchi, T., & Stewart, N. (2018). Multialternative decision by sampling: A model of decision making constrained by process data. Psychological Review, 125(4), 512–544.
Norton, J. D. (1991). Thought experiments in Einstein's work. In T. Horowitz & G. Massey (Eds.), Thought experiments in science and philosophy (pp. 129–148). Lanham: Rowman & Littlefield.
Oaksford, M. (1988). Cognition and enquiry: The pragmatics of conditional reasoning (Doctoral dissertation). Centre for Cognitive Science, University of Edinburgh.
Oaksford, M. (2025). Social rationality and human reasoning: Expressivism and the flat mind. Topics in Cognitive Science, 17(3), 636–661. https://doi.org/10.1111/tops.12757.
Oaksford, M., & Chater, N. (1994). A rational analysis of the selection task as optimal data selection. Psychological Review, 101, 608–631.
Oaksford, M., & Chater, N. (1998). Rational models of cognition. Oxford, England: Oxford University Press.
Oaksford, M., & Chater, N. (2007). Bayesian rationality: The probabilistic approach to human reasoning. Oxford, England: Oxford University Press.
Oaksford, M., & Chater, N. (2013). Dynamic inference and everyday conditional reasoning in the new paradigm. Thinking and Reasoning, 19, 346–379. https://doi.org/10.1080/13546783.2013.808163.
Oaksford, M., & Chater, N. (2017). Causal models and conditional reasoning. In M. Waldmann (Ed.), Oxford handbook of causal reasoning (pp. 327–346). Oxford, England: Oxford University Press.
Oaksford, M., Chater, N., & Larkin, J. (2000). Probabilities and polarity biases in conditional inference. Journal of Experimental Psychology: Learning, Memory & Cognition, 26, 883–899.
Oaksford, M., & Hall, S. (2016). On the source of human irrationality. Trends in Cognitive Sciences, 20, 336–344.
Osherson, D. N., Stob, M., & Weinstein, S. (1985). Systems that learn: An introduction to learning theory for cognitive and computer scientists. Cambridge, MA: MIT Press.
Pearl, J. (1988). Probabilistic reasoning in intelligent systems. San Mateo, CA: Morgan Kaufman.
Pearl, J. (2000). Causality. Cambridge, UK: Cambridge University Press.
Pinker, S. (1989). Learnability and cognition: The acquisition of argument structure. Cambridge, MA: MIT Press.
Pinker, S. (1994). The language instinct: How the mind creates language. New York, NY: William Morrow and Company.
Pinker, S., & Bloom, P. (1990). Natural language and natural selection. Behavioral and Brain Sciences, 13(4), 707–784.
Priest, G., Tanaka, K., & Weber, Z. (2022). Paraconsistent Logic. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2022 ed.). Standford, CA: Stanford University. https://plato.stanford.edu/archives/spr2022/entries/logic‐paraconsistent/.
Rao, R. P., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra‐classical receptive‐field effects. Nature Neuroscience, 2(1), 79–87.
Rawls, J. (1971). A theory of justice. Cambridge, MA: Harvard University Press.
Rips, L. J. (1994). The psychology of proof: Deductive reasoning in human thinking. Cambridge, MA: The MIT Press.
Rumelhart, D. E. (1980). Schemata: The building blocks of cognition. In R. J. Spiro, B. C. Bruce, & W. F. Brewer (Eds.), Theoretical issues in reading comprehension (pp. 33–58). Abingdon, UK: Routledge.
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back‐propagating errors. Nature, 323(6088), 533–536.
Rumelhart, D. E., & McClelland, J. L. L. (1986). On learning the past tenses of English verbs. In D. E. Rumelhart & J. L. McClelland (Eds.), Parallel distributed processing: Explorations in the microstructures of cognition (Vol. 2, pp. 216–271). Cambridge, MA: MIT Press.
Rumelhart, D. E., & McClelland, J. L. & the PDP Research Group. (1986) Parallel distributed processing: Explorations in the microstructures of cognition (2 volumes). Cambridge, MA: MIT Press.
Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. (1986). Sequential thought processes in PDP models. In D. E. Rumelhart & J. L. McClelland (Eds.), Parallel distributed processing: Explorations in the microstructures of cognition (Vol. 2, pp. 3–57). Cambridge, MA: MIT Press.
Sanborn, A. N., & Chater, N. (2016). Bayesian brains without probabilities. Trends in Cognitive Sciences, 20(12), 883–893.
Schelling, T. C. (1960). The strategy of conflict. Cambridge, MA: Harvard University Press.
Scholten, M., & Read, D. (2010). The psychology of intertemporal tradeoffs. Psychological Review, 117(3), 925–944.
Shafto, P., Goodman, N. D., & Griffiths, T. L. (2014). A rational account of pedagogical reasoning: Teaching by, and learning from, examples. Cognitive Psychology, 71, 55–89.
Sedgewick, R., & Wayne, K. (2022). Algorithms (4th ed.). Cambridge, MA: MIT Press.
Sen, A. K. (1977). Rational fools: A critique of the behavioral foundations of economic theory. Philosophy and Public Affairs, 6(4), 317–344.
Sengupta, P., & Garrity, P. (2013). Sensing temperature. Current Biology, 23(8), R304–R307.
Sher, S., & McKenzie, C. R. (2006). Information leakage from logically equivalent frames. Cognition, 101(3), 467–494.
Skinner, B. F. (1957). Verbal behavior. Norwalk, CT: Appleton‐Century‐Crofts.
Sloman, S., Rottenstreich, Y., Wisniewski, E., Hadjichristidis, C., & Fox, C. R. (2004). Typical versus atypical unpacking and superadditive probability judgment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(3), 573–582.
Solomonoff, R. J. (1978). Complexity‐based induction systems: Comparisons and convergence theorems. IEEE Transactions on Information Theory, IT24, 422–432.
Sperber, D., Cara, F., & Girotto, V. (1995). Relevance theory explains the selection task. Cognition, 57(1), 31–95.
Stewart, N. (2009). EPS prize lecture: Decision by sampling: The role of the decision environment in risky choice. Quarterly Journal of Experimental Psychology, 62(6), 1041–1062.
Stewart, N., Brown, G. D. A., & Chater, N. (2005). Absolute identification by relative judgment. Psychological Review, 112, 881–911.
Stewart, N., Chater, N., & Brown, G. D. A. (2006). Decision by sampling. Cognitive Psychology, 53, 1–26.
Taylor, F. S. (1942). The origin of the thermometer. Annals of Science, 5(2), 129–156.
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331(6022), 1279–1285.
Trujillo Jiménez, D., Zhang, M., Zhi‐Xuan, T., Tenenbaum, J. B., & Levine, S. (2025). Resource rational virtual bargaining for moral judgment: Towards a probabilistic cognitive model. Topics in Cognitive Science, 17(3), 713–738. https://doi.org/10.1111/tops.12781.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.
Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90(4), 293–315.
Vitányi, P. M., & Chater, N. (2017). Identification of probabilities. Journal of Mathematical Psychology, 76, 13–24.
Vul, E., Goodman, N.D., Griffiths, T. L., & Tenenbaum, J. B. (2014). One and done? Optimal decisions from very few samples. Cognitive Science, 38(4), 599–637.
Walasek, L., & Brown, G. D. (2023). Incomparability and incommensurability in choice: No common currency of value? Perspectives on Psychological Science, 19(6), 1011–1030. https://doi.org/10.1177/17456916231192828.
Yang, Y., & Piantadosi, S. T. (2022). A model for learning strings is not a model of language. Proceedings of the National Academy of Sciences, 119(12), e2201651119.
Zeitoun, H., Melkonyan, T., & Chater, N. (2023). The social contract in miniature: How virtual bargaining supports team production. Academy of Management Review, 48(3), 432–462.
Zhu, J. ‐Q., Sanborn, A., & Chater, N. (2020). The Bayesian sampler: Generic Bayesian inference causes incoherence in human probability judgments. Psychological Review, 127(5), 719–748.
Zhu, J. ‐Q., Sundh, J., Spicer, J., Chater, N., & Sanborn, A. N. (2024). The autocorrelated Bayesian sampler: A rational process for probability judgments, estimates, confidence intervals, choices, confidence judgments, and response times. Psychological Review, 131(2), 456–493.
Zuidema, W. (2002). How the poverty of the stimulus solves the poverty of the stimulus. In S. Becker, S. Thrun, & K. Obermayer (Eds.) Advances in Neural Information Processing Systems (Vol. 15, pp. 51–58). MIT Press. https://proceedings.neurips.cc/paper_files/paper/2002/hash/04ad5632029cbfbed8e136e5f6f7ddfa‐Abstract.html.
Grant Information:
101120763 UK Research and Innovation/EU Horizon TANGO
Contributed Indexing:
Keywords: Coordination; Decision‐making; Game theory; Inconsistency; Paradox; Rationality; Reasoning
Entry Date(s):
Date Created: 20250401 Date Completed: 20250729 Latest Revision: 20250729
Update Code:
20250731
DOI:
10.1111/tops.70004
PMID:
40166970
Database:
MEDLINE
Weitere Informationen
How should we identify interesting topics in cognitive science? This paper suggests that one useful research strategy is to hunt for, and attempt to resolve, paradoxes: that is, apparent or real contradictions in our understanding of the mind and of thought. The rationale for this strategy is the assumption that our current thinking, and our various partial theories, of any topic are typically ill-defined, inconsistent or both. Thus, contradictions and confusions abound. Isolating paradoxes helps us expose vagueness and contradictions and demands that we formulate our ideas more precisely. From this point of view, finding a robust and puzzling contradiction in our current thinking should be celebrated as an achievement in itself. Ideally, of course, we then make further progress by clarifying how the paradox may be resolved, by clarifying our theories or finding new data that may decide between inconsistent assumptions. This approach is illustrated through examples from the author's research over several decades, which seems in retrospect to involve a repeated, if largely unwitting, application of this strategy.
(© 2025 The Author(s). Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.)