Publications: 
Computational Principles of Intelligence

Haridi, S.; Wu, C.; Dasgupta, I.; Schulz, E.: The scaling of mental computation in a sorting task. Cognition 241, 105605 (2023)

Giron, A.; Ciranka, S.; Schulz, E.; van den Bos, W.; Ruggeri, A.; Meder, B.; Wu, C.: Developmental changes in exploration resemble stochastic optimization. Nature Human Behaviour 7 (11), pp. 1955 - 1967 (2023)

Binz, M.; Schulz, E.: Reconstructing the Einstellung effect. Computational Brain & Behavior 6 (3), pp. 526 - 542 (2023)

Brändle, F.; Stocks, L.; Tenenbaum, J.; Gershman, S.; Schulz, E.: Empowerment contributes to exploration behaviour in a creative video game. Nature Human Behaviour 7 (9), pp. 1481 - 1489 (2023)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Chunking as a rational solution to the speed-accuracy trade-off in a serial reaction time task. Scientific Reports 13, 7680 (2023)

Garvert, M.; Saanum, T.; Schulz, E.; Schuck, N.; Doeller, C.: Hippocampal spatio-predictive cognitive maps adaptively guide reward generalization. Nature Neuroscience 26 (4), pp. 615 - 626 (2023)

Binz, M.; Schulz, E.: Using cognitive psychology to understand GPT-3. Proceedings of the National Academy of Sciences of the United States of America 120 (6), e2218523120 (2023)

Schreiber, A.; Wu, S.; Wu, C.; Indiveri, G.; Schulz, E.: Biologically-plausible hierarchical chunking on mixed-signal neuromorphic hardware. In: NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms. NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms, New Orleans, LA, USA, December 16, 2023. (2023)

Brändle, F.; Schulz, E.; Wu, C.: Learning progress and uncompensated rewards as motivational drivers of engagement. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.114, pp. 832 - 835. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Haridi, S.; Thalmann, M.; Schulz, E.: Simulating the Scaling of Long-Term Memory Retrieval. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.101, pp. 784 - 787. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Hedrich, N.; Hall-McMaster, S.; Schulz, E.; Schuck, N.: Faster learning from slow features: The temporal coherence prior in human reinforcement learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.10, pp. 458 - 461. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Ludwig, T.; Siegel, M.; Schulz, E.: Human Multi-Task Learning: the Why and What. In: 2023 Conference on Cognitive Computational Neuroscience, P-1.119, pp. 418 - 421. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: A Rational Analysis of the Optimism Bias using Meta-Reinforcement Learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.37, pp. 557 - 559. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Schulze Buschoff, L.; Schulz, E.; Binz, M.: The Acquisition of Physical Knowledge in Generative Neural Networks. In: 40th International Conference on Machine Learning, pp. 30321 - 30341 (Eds. Krause, A.; Brunskill, E.; Cho, K.; Engelhardt, B.; Sabato, S. et al.). Fortieth International Conference on Machine Learning (ICML 2023), Honolulu, HI,USA, July 23, 2023 - July 29, 2023. (2023)

Thalmann, M.; Schulz, E.: Simple, Idiosyncratic Decision Heuristics in a Two-Armed Bandit Task. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.80, pp. 1156 - 1159. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Witte, K.; Schulz, E.; Wise, T.; Huys, Q.: People who worry more explore more. In: 2023 Conference on Cognitive Computational Neuroscience, P-1.101, pp. 355 - 357. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Wu, S.; Thalmann, M.; Schulz, E.: Projectional motifs facilitate sequence memorization and transfer. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.118, pp. 1294 - 1296. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Binz, M.; Schulz, E.: Modeling Human Exploration Through Resource-Rational Reinforcement Learning. In: Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), pp. 31755 - 31768 (Eds. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, November 28, 2022 - December 09, 2022. Curran, Red Hook, NY, USA (2023)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), pp. 36706 - 36721 (Eds. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, November 28, 2022 - December 09, 2022. Curran, Red Hook, NY, USA (2023)

Binz, M.; Schulz, E.: Using cognitive psychology to understand GPT-3. In 29th Biennial Subjective Probability Utility and Decision Making Conference (SPUDM 2023), p. 31. 29th Biennial Subjective Probability Utility and Decision Making Conference (SPUDM 2023), Wien, Austria, August 20, 2023 - August 24, 2023. (2023)