Using reinforcement-based models of transitive inference to simulate primate data Clara Bergene, Olga F. Lazareva (Drake University), Regina Paxton Gazes (Zoo Atlanta), Robert Hampton (Emory University) Background Transitive inference is the ability to deduce that if A > B, and B > C, then A > C Example of deductive reasoning In nonverbal tasks, can be explained by appealing to reinforcement history Reinforcement-based models (Wynne, Siemann-Delius) have been used to accurately predict pigeons’ performance on the tasks Less is known about the ability of reinforcement-based model to predict primate data Our goal Test predictive ability of Siemann-Delius and Wynne models using primate data for seven-item series with backward training and list linking training Simulation details Used both Wynne model and Siemann-Delius model (only Siemann-Delius presented) Selected a combination of free parameters that produced best fit for training data Used these parameters and accrued associative values to predict testing performance on subject-by-subject basis List linking training F+ G-, E+ F-, D+ E-, C+ D-, B+ C-, A+ B- M+ N-, L+ M-, K+ L-, J+ K-, I+ J-, H+ I- Linking pair: G+ H- Tested using within-list pairs (e.g., BD or IM) and between-list pairs (e.g., BI) Data collected at Hampton’s lab (Emory University) 12 adult rhesus macaques (Macaca mulatta) Seven-item sequential backward training F+ G-, E+ F-, D+ E-, C+ D-, B+ C-, A+ B- Tested using all novel pairs Training details Results: List Linking Captures the difference between end-anchor pairs and inner pairs Correctly predicts between-list pairs and within-list pairs for List 1 (A…G) Does not predict within-list pairs for List 2 (H…M) Possibly due to list linking procedure Results: Sequential backward training (averaged across A…G list and H…M list) Captures difference between the end-anchor and the inner pairs Predicts opposite to symbolic distance effect Possibly due to the lack of correction trials or to the backward order of presentation Sequential backward training with mock correction trials List linking, mock List 2 training only Randomly added 1-3 correction trials after each incorrect choice and repeated simulations Results similar to initial simulations Run simulations using List 2 training sequence without list linking procedure, and only with initial training Predicts better performance, but still well below monkeys’ performance Low performance in List 2 cannot be attributed to list linking procedure alone Conclusions Associative models can fit sequential backward training data obtained with pigeons, but not with primates Possibly due to quicker learning in primates In list linking, the models provide a good fit for between-list pairs that were assumed to be challenging They do not, however, predict performance in within-list pairs for List 2 (H…M) This failure cannot be attributed solely to list linking procedure Pattern of results suggests contribution from associative values augmented by another process Sequential backward training in mock forward order Coded the data in reversed order (F+ G- as A+ B-, and so on) and repeated simulations Does not predict any difference between end-anchor pairs and inner pairs Correctly predicts the direction of symbolic distance effect Backward order of presentation in primates appears to provide a good control for reinforcement history Acknowledgments This research was supported by the A&S Drake University Faculty Development Research grant to OFL