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For example, do connectionist networks describe processes (McClelland et al., 2010) or functions (Griffiths, Chater, Kemp, Perfors, & Tenenbaum, 2010)? Is the recognition heuristic (Goldstein & Gigerenzer, 2002) a process model (Pohl, 2011)? Our aim in the present article is to provide a framework to clarify the requirements of cognitive process models in general.

Simultaneously, psychologists debate which cognitive models constitute process models (Brandstätter, Gigerenzer, & Hertwig, 2006). To date, not much advice exists on the general development of cognitive process models (see Grüne-Yanoff, 2014), besides very broad overviews (e.g., Sun, 2008), and very model-specific implementation tutorials (e.g., Griffiths & Yuille, 2008 Pothos & Busemeyer, 2013). By “process,” we refer to the change of the state of (cognitive) systems over time (Hartmann, 1996). This trend shows that investigating mental processes is considered relevant and useful to understand human cognition by many psychologists. Moreover, the framework can advance currently unresolved debates about which models belong to the category of process models. It can be a guideline for developing cognitive process models. This framework can be used for refining models before testing them or after testing them empirically, and it does not rely on specific modeling paradigms.

Lastly, process models require a conceptual scope specifying levels of abstraction for the information entering the mind, the proposed mental events, and the behavior of interest. Moreover, the presumed information transformation steps are not contradicting current knowledge of human cognitive capacities. The models’ predictions for the processes can be derived from the input, without reverse inference from the output data. They make predictions not only for the behavior of interest but also for processes. They specify a hypothesized mental information transformation.

We argue that the following dimensions characterize process models: They have a scope that includes different levels of abstraction. Process models model not only inputs and outputs but also model the ongoing information transformations at a given level of abstraction. This paper proposes a framework for characterizing and building cognitive process models. The term process model is widely used, but rarely agreed upon.