Humans often generalize rewarding experiences across abstract social roles. Theories of reward learning suggest that people generalize through model-based learning, but such learning is cognitively costly. Why do people seem to generalize across social roles with ease? Humans are social experts who easily recognize social roles that reflect familiar semantic concepts (e.g., “helper” or “teacher”). People may associate these roles with model-free reward (e.g., learning that helpers are rewarding), allowing them to generalize easily (e.g., interacting with novel individuals identified as helpers). In four online experiments with U.S. adults (N = 577), we found evidence that social concepts ease complex learning (people generalize more and at faster speed) and that people attach reward directly to abstract roles (they generalize even when roles are unrelated to task structure). These results demonstrate how familiar concepts allow complex behavior to emerge from simple strategies, highlighting social interaction as a prototype for studying cognitive ease in the face of environmental complexity.
BarsalouL. W. (1983). Ad hoc categories. Memory & Cognition, 11(3), 211–227.
4.
BatesD.MächlerM.BolkerB.WalkerS. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1). https://doi.org/10.18637/jss.v067.i01
5.
BehrensT. E. J.MullerT. H.WhittingtonJ. C. R.MarkS.BaramA. B.StachenfeldK. L.Kurth-NelsonZ. (2018). What is a cognitive map? Organizing knowledge for flexible behavior. Neuron, 100(2), 490–509.
6.
BoormanE. D.SweigartS. C.ParkS. A. (2021). Cognitive maps and novel inferences: A flexibility hierarchy. Current Opinion in Behavioral Sciences, 38, 141–149.
7.
BrownT. I.CarrV. A.LaRocqueK. F.FavilaS. E.GordonA. M.BowlesB.BailensonJ. N.WagnerA. D. (2016). Prospective representation of navigational goals in the human hippocampus. Science, 352(6291), 1323–1326.
8.
CamererC. F. (1981). The validity and utility of expert judgment. The University of Chicago.
9.
CosmidesL. (1989). The logic of social exchange: Has natural selection shaped how humans reason? Studies with the Wason selection task. Cognition, 31(3), 187–276.
10.
CushmanF.MorrisA. (2015). Habitual control of goal selection in humans. Proceedings of the National Academy of Sciences, USA, 112(45), 13817–13822.
11.
DawN. D.GershmanS. J.SeymourB.DayanP.DolanR. J. (2011). Model-based influences on humans’ choices and striatal prediction errors. Neuron, 69(6), 1204–1215.
12.
DiukC.TsaiK.WallisJ.BotvinickM.NivY. (2013). Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia. Journal of Neuroscience, 33(13), 5797–5805.
DollB. B.SimonD. A.DawN. D. (2012). The ubiquity of model-based reinforcement learning. Current Opinion in Neurobiology, 22(6), 1075–1081.
15.
DuncanK.DollB. B.DawN. D.ShohamyD. (2018). More than the sum of its parts: A role for the hippocampus in configural reinforcement learning. Neuron, 98(3), 645–657.
16.
DunsmoorJ. E.MurphyG. L. (2014). Stimulus typicality determines how broadly fear is generalized. Psychological Science, 25(9), 1816–1821.
17.
EcksteinM. K.CollinsA. G. (2020). Computational evidence for hierarchically structured reinforcement learning in humans. Proceedings of the National Academy of Sciences, USA, 117(47), 29381–29389.
18.
EconomidesM.Kurth-NelsonZ.LübbertA.Guitart-MasipM.DolanR. J. (2015). Model-based reasoning in humans becomes automatic with training. PLOS Computational Biology, 11(9), Article e1004463. https://doi.org/10.1371/journal.pcbi.1004463
19.
Feher da SilvaC.HareT. A. (2020). Humans primarily use model-based inference in the two-stage task. Nature Human Behaviour, 4(10), 1053–1066.
20.
FeldmanHallO.NassarM. R. (2021). The computational challenge of social learning. Trends in Cognitive Sciences, 25(12), 1045–1057.
21.
GentnerD. (2016). Language as cognitive tool kit: How language supports relational thought. American Psychologist, 71(8), 650–657. https://doi.org/10.1037/amp0000082
22.
GentnerD.AnggoroF. K.KlibanoffR. S. (2011). Structure mapping and relational language support children’s learning of relational categories: Structure mapping and relational language. Child Development, 82(4), 1173–1188.
23.
GentnerD.KurtzK. J. (2005). Relational categories. In AhnW.GoldstoneR. L.LoveB. C.MarkmanA. B.WolffP. (Eds.), Categorization inside and outside the laboratory: Essays in honor of Douglas L. Medin (pp. 151–175). American Psychological Association. https://doi.org/10.1037/11156-009
24.
GickM. L.HolyoakK. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15(1), 1–38.
25.
GileadM.TropeY.LibermanN. (2019). Above and beyond the concrete: The diverse representational substrates of the predictive brain. Behavioral and Brain Sciences, 43, Article e121. https://doi.org/10.1017/S0140525X19002000
26.
GillanC. M.OttoA. R.PhelpsE. A.DawN. D. (2015). Model-based learning protects against forming habits. Cognitive, Affective, & Behavioral Neuroscience, 15(3), 523–536.
27.
GoldwaterM. B.GentnerD.LaDueN. D.LibarkinJ. C. (2021). Analogy generation in science experts and novices. Cognitive Science, 45(9), Article e13036. https://doi.org/10.1111/cogs.13036
28.
GoldwaterM. B.MarkmanA. B.StilwellC. H. (2011). The empirical case for role-governed categories. Cognition, 118(3), 359–376.
29.
HackelL. M.BergJ. J.LindströmB. R.AmodioD. M. (2019). Model-based and model-free social cognition: Investigating the role of habit in social attitude formation and choice. Frontiers in Psychology, 10, Article 2592. https://doi.org/10.3389/fpsyg.2019.02592
30.
HackelL. M.KogonD.AmodioD. M.WoodW. (2022). Group value learned through interactions with members: A reinforcement learning account. Journal of Experimental Social Psychology, 99, Article 104267. https://doi.org/10.1016/j.jesp.2021.104267
31.
HackelL. M.Mende-SiedleckiP.AmodioD. M. (2020). Reinforcement learning in social interaction: The distinguishing role of trait inference. Journal of Experimental Social Psychology, 88, Article 103948. https://doi.org/10.1016/j.jesp.2019.103948
32.
HackelL. M.ZakiJ. (2018). Propagation of economic inequality through reciprocity and reputation. Psychological Science, 29(4), 604–613.
33.
HafriA.FirestoneC. (2021). The perception of relations. Trends in Cognitive Sciences, 25(6), 475–492.
34.
HeiderF. (1958). The psychology of interpersonal relations. Wiley.
35.
HolyoakK. J. (2012). Analogy and relational reasoning. In HolyoakK. J.MorrisonR. G. (Eds.), The Oxford handbook of thinking and reasoning (pp. 234–259). Oxford University Press.
36.
KalksteinD. A.BoschD. A.KleimanT. (2020). The contrast diversity effect: Increasing the diversity of contrast examples increases generalization from a single item. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46(2), 296–315.
37.
KalksteinD. A.HackelL. M.TropeY. (2020). Person-centered cognition: The presence of people in a visual scene promotes relational reasoning. Journal of Experimental Social Psychology, 90, 104009. https://doi.org/10.1016/j.jesp.2020.104009
38.
KalksteinD. A.KleimanT.WakslakC. J.LibermanN.TropeY. (2016). Social learning across psychological distance. Journal of Personality and Social Psychology, 110(1), 1–19.
39.
KaragozA. B.ReaghZ. M.KoolW. (2022). The construction and use of cognitive maps in model-based control. PsyArXiv. https://doi.org/10.31234/osf.io/ngqwa
40.
KoolW.GershmanS. J.CushmanF. A. (2017). Cost-benefit arbitration between multiple reinforcement-learning systems. Psychological Science, 28(9), 1321–1333.
41.
KoolW.GershmanS. J.CushmanF. A. (2018). Planning complexity registers as a cost in metacontrol. Journal of Cognitive Neuroscience, 30(10), 1391–1404.
42.
LoewensteinJ.GentnerD. (2005). Relational language and the development of relational mapping. Cognitive Psychology, 50(4), 315–353.
43.
MasonM. F.MageeJ. C.KuwabaraK.NindL. (2010). Specialization in relational reasoning: The efficiency, accuracy, and neural substrates of social versus nonsocial inferences. Social Psychological and Personality Science, 1(4), 318–326.
44.
MoreyR. D. (2008). Confidence intervals from normalized data: A correction to Cousineau (2005). Tutorials in Quantitative Methods for Psychology, 4, 61–64.
45.
MurphyG. L.MedinD. L. (1985). The role of theories in conceptual coherence. Psychological Review, 92(3), 289–316.
OttoA. R.GershmanS. J.MarkmanA. B.DawN. D. (2013). The curse of planning: Dissecting multiple reinforcement-learning systems by taxing the central executive. Psychological Science, 24(5), 751–761.
48.
ParkS. A.MillerD. S.BoormanE. D. (2021). Inferences on a multidimensional social hierarchy use a grid-like code. Nature Neuroscience, 24(9), 1292–1301.
49.
PrecupD.SuttonR. S. (1997). Multi-time models for temporally abstract planning. In JordanM. I.KearnsM. J.SollaS. A. (Eds.), Proceedings of the 10th International Conference on Neural Information Processing Systems (pp. 1050–1056). Association for Computing Machinery.
50.
R Core Team. (2016). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing.
51.
ReadS. J. (1987). Constructing causal scenarios: A knowledge structure approach to causal reasoning. Journal of Personality and Social Psychology, 52(2), 288–302.
ShaharN.MoranR.HauserT. U.KievitR. A.McNameeD.MoutoussisM., NSPN Consortium, & DolanR. J. (2019). Credit assignment to state-independent task representations and its relationship with model-based decision making. Proceedings of the National Academy of Sciences, USA, 116(32), 15871–15876.
54.
SpuntR. P.AdolphsR. (2015). Folk explanations of behavior: A specialized use of a domain-general mechanism. Psychological Science, 26(6), 724–736.
55.
TodorovA.UlemanJ. S. (2002). Spontaneous trait inferences are bound to actors’ faces: Evidence from a false recognition paradigm. Journal of Personality and Social Psychology, 83(5), 1051–1065.
56.
WangF.SchoenbaumG.KahntT. (2020). Interactions between human orbitofrontal cortex and hippocampus support model-based inference. PLOS Biology, 18(1), Article e3000578. https://doi.org/10.1371/journal.pbio.3000578
57.
WinterL.UlemanJ. S. (1984). When are social judgments made? Evidence for the spontaneousness of trait inferences. Journal of Personality and Social Psychology, 47(2), 237–252.
58.
WrightJ. C.MurphyG. L. (1984). The utility of theories in intuitive statistics: The robustness of theory-based judgments. Journal of Experimental Psychology: General, 113(2), 301–322.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
