1. Angelos-Miltiadis Krypotos, Tom Beckers, Merel Kindt & Eric-Jan Wagenmakers (forthcoming). A Bayesian Hierarchical Diffusion Model Decomposition of Performance in Approach–Avoidance Tasks. Cognition and Emotion:1-21.
  2. Hongjing Lu, Randall R. Rojas, Tom Beckers & Alan L. Yuille (2015). A Bayesian Theory of Sequential Causal Learning and Abstract Transfer. Cognitive Science 39 (4):n/a-n/a.
    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that (...)
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  3. Tom Beckers & Bram Vervliet (2009). The Truth and Value of Theories of Associative Learning. Behavioral and Brain Sciences 32 (2):200-201.
    In this commentary, we assess the propositional approach to associative learning not only in terms of veridicality and falsifiability, but also in heuristic value. We remark that it has furthered our knowledge and understanding of human, as well as animal, associative learning. At the same time, we maintain that models developed from the association formation tradition continue to bear great heuristic value as well.
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