(a) Performance as a function of trial number for Rules 1 and 3 (combined), for congruent and incongruent trials. (b) Performance for Rules 1 and 3 (combined, first 50 trials), as a function of the morph level for both color (relevant) and shape (irrelevant) features. Gray boxes highlight congruent stimuli, red boxes highlight incongruent stimuli. (c) Performance for Rule 2, as a function of the morph level for both color (relevant) and shape (irrelevant) features. Note the lack of an incongruency effect. (d–f) Same as a–c but for the QL model. (g–i) Same as a–c for the IO model. (j–l) Same as a–c but for the HQL model. Statistics on Monkey C: During early trials of Rules 1 and 3, the monkeys’ performance was significantly higher for congruent trials than for incongruent trials (gray vs. red squares; 93%, confidence interval, CI = [0.91,0.95] vs. 49%, CI = [0.47,0.51], respectively; with Δ = 44; Fisher’s test p < 10−4). There was no difference in performance between congruent and incongruent stimuli during Rule 2 (gray vs. red squares; performance was 94%, CI = [0.91,0.95], and 91%, CI = [0.89,0.92], respectively; with Δ = 2.7; Fisher’s test p = 0.07). Statistics of QL model fitted on Monkey C: The model performed worse on congruent than incongruent trials in Rules 1 and 3 (41% and 52%, respectively; Δ = −10; Fisher’s test p < 10−4), against our behavioral observations. Furthermore, the model produced a difference in performance during Rule 2 (48% for congruent vs. 54% for incongruent; Δ = −6.1; Fisher’s test p < 10−4). Statistics of IO model fitted on Monkey C: Learning quickly reached a low asymptotic performance in Rules 1 and 3, for both congruent and incongruent trials (69% and 67% respectively; Δ = 2.5 only). Statistics of HQL model fitted on Monkey C: The model reproduced the greater performance on congruent than incongruent stimuli in Rules 1 and 3 (94% and 53%, respectively; Δ = 41). It also captured the absence of incongruency effect in Rule 2 (green vs. red squares; 91% and 91%, respectively; Δ = 0.081).