Thinking of learning phenomena as instances of relational behavior.

Jan De Houwer, Martin Finn, Matthias Raemaekers, Jamie Cummins, Yannick Boddez
Author Information
  1. Jan De Houwer: Ghent University, Ghent, Belgium. jan.dehouwer@ugent.be. ORCID
  2. Martin Finn: Ghent University, Ghent, Belgium.
  3. Matthias Raemaekers: Ghent University, Ghent, Belgium.
  4. Jamie Cummins: Ghent University, Ghent, Belgium.
  5. Yannick Boddez: Ghent University, Ghent, Belgium.

Abstract

We explore the idea that some learning phenomena can be thought of as instances of relational behavior-more specifically, arbitrarily applicable relational responding (AARR). After explaining the nature of AARR, we discuss what it means to say that learning phenomena such as evaluative and fear conditioning are instances of AARR. We then list several implications of this perspective for empirical and theoretical research on learning, as well as for how learning phenomena relate to other psychological phenomena in human and nonhuman animals.

Keywords

References

  1. Barnes-Holmes, D., & Barnes-Holmes, Y. (2000). Explaining complex behavior: Two perspectives on the concept of generalized operant classes. The Psychological Record, 50, 251–265. [DOI: 10.1007/BF03395355]
  2. Barnes-Holmes, D., & Harte, C. (2022). Relational frame theory 20 years on: The Odysseus voyage and beyond. Journal of the Experimental Analysis of Behavior, 117, 240–266. https://doi.org/10.1002/jeab.733 [DOI: 10.1002/jeab.733]
  3. Boddez, Y., De Houwer, J., & Beckers, T. (2017). The inferential reasoning theory of causal learning: Towards a multi-process propositional account. In M. Waldmann (Ed.), The Oxford handbook of causal reasoning (pp. 1–22). Oxford University Press.
  4. Boddez, Y., Finn, M., & De Houwer, J. (2021). The (shared) features of fear: Toward the source of human fear responding. Current Opinion in Psychology, 41, 113–117. [DOI: 10.1016/j.copsyc.2021.07.005]
  5. Bolles, R. C. (1972). The avoidance learning problem. Psychology of Learning and Motivation, 6, 97–145. [DOI: 10.1016/S0079-7421(08)60385-0]
  6. Bouton, M. E. (2016). Learning and behavior: A contemporary synthesis (2nd ed.). Sinauer Associates.
  7. Catania, A. C. (2013). Learning (5th ed.). Sloan Publishing.
  8. De Houwer, J. (2007). A conceptual and theoretical analysis of evaluative conditioning. The Spanish Journal of Psychology, 10, 230–241. [DOI: 10.1017/S1138741600006491]
  9. De Houwer, J. (2009). The propositional approach to associative learning as an alternative for association formation models. Learning & Behavior, 37, 1–20. [DOI: 10.3758/LB.37.1.1]
  10. De Houwer, J. (2018). Propositional models of evaluative conditioning. Social Psychological Bulletin, 13(3), e28046. https://doi.org/10.5964/spb.v13i3.28046 [DOI: 10.5964/spb.v13i3.28046]
  11. De Houwer, J., & Hughes, S. (2016). Evaluative conditioning as a symbolic phenomenon: On the relation between evaluative conditioning, evaluative conditioning via instructions, and persuasion. Social Cognition, 34, 480–494. [DOI: 10.1521/soco.2016.34.5.480]
  12. De Houwer, J., & Hughes, S. (2017). Environmental regularities as a concept for carving up the realm of learning research: Implications for relational frame theory. Journal of Contextual Behavioral Science, 6, 343–346. [DOI: 10.1016/j.jcbs.2016.07.002]
  13. De Houwer, J., & Hughes, S. (2020). The psychology of learning: A functional-cognitive introduction. The MIT Press.
  14. De Houwer, J., & Hughes, S. (2022). Learning in individual organisms, genes, machines, and groups: A new way of defining and relating learning in different systems. Perspectives on Psychological Science. Advance online publication. https://doi.org/10.1177/17456916221114886 .
  15. De Houwer, J., Barnes-Holmes, D., & Moors, A. (2013). What is learning? On the nature and merits of a functional definition of learning. Psychonomic Bulletin & Review, 20, 631–642. https://doi.org/10.3758/s13423-013-0386-3 [DOI: 10.3758/s13423-013-0386-3]
  16. De Houwer, J., Hughes, S., & Barnes-Holmes, D. (2016). Associative learning as higher-order cognition: Learning in human and nonhuman animals from the perspective of propositional theories and relational frame theory. Journal of Comparative Psychology, 130, 215–225. [DOI: 10.1037/a0039999]
  17. De Houwer, J., Van Dessel, P., & Moran, T. (2020). Attitudes beyond associations: On the role of propositional representations in stimulus evaluation. Advances in Experimental Social Psychology, 61, 127–183. [DOI: 10.1016/bs.aesp.2019.09.004]
  18. Dixon, M. R. (2016). The PEAK relational training system: Transformation module. Shawnee Scientific Press.
  19. Doumas, L. A., & Martin, A. E. (2018). Learning structured representations from experience. In K. Federmeier (Ed.), Psychology of learning and motivation (Vol. 69, pp. 165–203). Academic Press.
  20. Doumas, L. A., Puebla, G., Martin, A. E., & Hummel, J. E. (in press). A theory of relation learning and cross-domain generalization. Psychological Review.
  21. Dymond, S., & Barnes, D. (1996). A transformation of self-discrimination response functions in accordance with the arbitrarily applicable relations of sameness and opposition. The Psychological Record, 46, 271–300.
  22. Hayes, S. C., & Sanford, B. T. (2014). Cooperation came first: Evolution and human language and cognition. Journal of the Experimental Analysis of Behavior, 101, 112–129. https://doi.org/10.1002/jeab.64 [DOI: 10.1002/jeab.64]
  23. Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. Kluwer. [DOI: 10.1007/b108413]
  24. Hughes, S., & Barnes-Holmes, D. (2014). Associative concept learning, stimulus equivalence, and relational frame theory: Working out the similarities and differences between human and nonhuman behavior. Journal of the Experimental Analysis of Behavior, 101, 156–160. [DOI: 10.1002/jeab.60]
  25. Hughes, S., & Barnes-Holmes, D. (2016). Relational frame theory: The basic account. In S. Hayes, D. Barnes-Holmes, R. Zettle, & T. Biglan (Eds.), Handbook of contextual behavioral science (pp. 129–178). Wiley.
  26. Hughes, S., De Houwer, J., & Barnes-Holmes, D. (2016a). The moderating impact of distal regularities on the effect of stimulus pairings: A novel perspective on evaluative conditioning. Experimental Psychology, 63, 20–44. [DOI: 10.1027/1618-3169/a000310]
  27. Hughes, S., De Houwer, J., & Perugini, M. (2016b). Expanding the boundaries of evaluative learning research: How intersecting regularities shape our likes and dislikes. Journal of Experimental Psychology: General, 145, 731–754. [DOI: 10.1037/xge0000100]
  28. Hughes, S., Ye, Y., & De Houwer, J. (2019). Evaluative conditioning effects are modulated by the nature of contextual pairings. Cognition & Emotion, 33, 871–884. [DOI: 10.1080/02699931.2018.1500882]
  29. Hughes, S., De Houwer, J., Mattavelli, S., & Hussey, I. (2020). The shared features principle: If two objects share a feature, people assume those objects also share other features. Journal of Experimental Psychology: General, 149, 2264–2288. [DOI: 10.1037/xge0000777]
  30. Lagnado, D. A., Waldmann, M. R., Hagmayer, Y., & Sloman, S. A. (2007). Beyond covariation: Cues to causal structure. In A. Gopnik & L. Schulz (Eds.), Causal learning: Psychology, philosophy, and computation (pp. 154–72). Oxford University Press.
  31. Leader, G., Barnes, D., & Smeets, P. M. (1996). Establishing equivalence relations using a respondent-type training procedure. The Psychological Record, 46(4), 685–706.
  32. McLaren, I. P., Forrest, C., McLaren, R., Jones, F., Aitken, M., & Mackintosh, N. (2014). Associations and propositions: The case for a dual-process account of learning in humans. Neurobiology of Learning and Memory, 108, 185–195. [DOI: 10.1016/j.nlm.2013.09.014]
  33. Mitchell, C. J., De Houwer, J., & Lovibond, P. F. (2009). The propositional nature of human associative learning. Behavioral and Brain Sciences, 32, 183–198. [DOI: 10.1017/S0140525X09000855]
  34. Moran, T., Nudler, Y., & Bar-Anan, Y. (in press). Evaluative conditioning: Past, present, and future. Annual Review of Psychology.
  35. Otten, S. (2016). The minimal group paradigm and its maximal impact in research on social categorization. Current Opinion in Psychology, 11, 85–89. [DOI: 10.1016/j.copsyc.2016.06.010]
  36. Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., Pentland, A., et al. (2019). Machine behaviour. Nature, 568, 477–486. https://doi.org/10.1038/s41586-019-1138-y [DOI: 10.1038/s41586-019-1138-y]
  37. Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. Classical Conditioning II: Current Research and Theory, 2, 64–99.
  38. Roychowdhury, S., Diligenti, M., & Gori, M. (2021). Regularizing deep networks with prior knowledge: A constraint-based approach. Knowledge-Based Systems, 222, 106989. [DOI: 10.1016/j.knosys.2021.106989]
  39. Schmajuk, N. A. (2010). Computational models of conditioning. Cambridge University Press. [DOI: 10.1017/CBO9780511760402]
  40. Sidman, M. (1971). Reading and auditory-visual equivalences. Journal of Speech and Hearing Research, 14, 5–13. [DOI: 10.1044/jshr.1401.05]
  41. Sidman, M. (1994). Equivalence relations and behavior: A research story. Authors Cooperative.
  42. Skinner, B. F. (1953). Science and human behavior. Macmillan.
  43. Skinner, B. F. (1966). An operant analysis of problem solving. In B. Kleinmutz (Ed.), Problem solving: Research, method and theory (pp. 225–257). Wiley.
  44. Steele, D., & Hayes, S. C. (1991). Stimulus equivalence and arbitrarily applicable relational responding. Journal of the Experimental Analysis of Behavior, 56(3), 519–555. [DOI: 10.1901/jeab.1991.56-519]
  45. Stewart, I., & McElwee, J. (2009). Relational responding and conditional discrimination procedures: An apparent inconsistency and clarification. The Behavior Analyst, 32, 309–317. [DOI: 10.1007/BF03392194]
  46. Zentall, T. R., Wasserman, E. A., & Urcuioli, P. J. (2014). Associative concept learning in animals. Journal of the Experimental Analysis of Behavior, 101, 130–151. https://doi.org/10.1002/jeab.55 [DOI: 10.1002/jeab.55]
  47. Zhang, C., Vinyals, O., Munos, R., & Bengio, S. (2018). A study on overfitting in deep reinforcement learning. ArXiv Preprint arXiv:1804.06893.

MeSH Term

Humans
Animals
Learning
Fear

Word Cloud

Created with Highcharts 10.0.0learningphenomenainstancesrelationalAARRconditioningbehaviorexploreideacanthoughtbehavior-morespecificallyarbitrarilyapplicablerespondingexplainingnaturediscussmeanssayevaluativefearlistseveralimplicationsperspectiveempiricaltheoreticalresearchwellrelatepsychologicalhumannonhumananimalsThinkingconceptualanalysis

Similar Articles

Cited By