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Cognitive Model for a Mental Folding Task (2023)
Preuss, Kai; Russwinkel, Nele (Contributor)
A simulated replication of the experiment was created for a cognitive model solving the mental folding task. The model was formalised and implemented in ACT-R, based on cognitive processes theorised by Shepard and Feng [1972]. Like the mental rotation model, it followed an outline proposed by Just and Carpenter [1976] comprised of visual encoding, transformation and comparison, and motor response. The mental folding model held several differences to its mental rotation counterpart. Contrary to the rotation model, no two separate strategy tracks were assumed by the folding model, making it more deterministic. Secondly, instead of alternating between comparison and transformation during folding processes, the mental folding model completed both necessary transformations (one for each arrow square), and afterwards initiated a single comparison process of the resulting structure to the reference stimulus. Akin to the mental rotation model however, instance-based learning [Gonzalez et al., 2003] was used to allow the model to skip the transformation process, thereby potentially shortening trial time: if the model recognised a target stimulus as being solved before and could remember its associated solution, spatial transformation was bypassed. In addition, visual shortcuts were possible if certain patterns were recognised (e.g., one arrow pointing to an empty square on one stimulus but not the other, or geometric relations between squares) and could be decided on by the model, with probability of choice mediated by a reinforcement learning algorithm included in ACT-R [Fu and Anderson, 2004].
The updated model focusses on modeling the data reported by Hilton et al., 2021, and contains bugfixes.
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