This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author's personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and f...

Business process simulation supports the improvement and analysis of business process models. Especially log generation features gain more and more attractivity, for instance, because of their applications in the evaluation of process mining techniques. Additionally, cognitive science has shown that examples promote the comprehension of abstract models. This is important especially for declarat...

We present AKIRA, an agent-based hybrid architecture designed for cognitive modeling. We describe some of the underlying ideas motivating its development, such as the possibility of exploiting distributed representations and performing parallel, dynamic and context aware computation. We illustrate its main components and capabilities and compare it with some related cognitive architectures, suc...

Conceptual models communicate the important aspects of a problem domain to stakeholders. The quality of the models is highly dependent on the usability of the modeling method used. This paper presents a survey conducted on a method that integrates the use of a semiformal notation, namely the Unified Modeling Language (UML) and a formal notation, namely B. The survey assessed the usability of th...

Meta-modeling platforms that support the automatic generation of modeling tools open a new quality in information systems development for engineers: Emphasis can be put on the design and use of a modeling language that is customized to the particular needs and desired features. This may contribute to strengthen the information system design phase as it helps to reduce the developers’ aversion a...

Cognitive modeling is a complex endeavor so it is not surprising that the goals and intentions of modelers are often misunderstood, even by other modelers. To try to clarify this we have attempted to map out the various philosophical and theoretical commitments that one makes when creating a cognitive model or architecture. The goal of this is to avoid misunderstandings between the adherents of...

Cognitive modeling is the distinguishing factor of cognitive science and the method of choice for formalizing human cognition. In order to bridge the gap between logic and human reasoning, a number of foundational research questions need to be rigorously answered. The objective of this paper is to present relevant concepts and to introduce possible modeling standards as well as key discussion p...

This paper describes a cognitive modeling effort for the O’Hare Modernization Project (OMP). Beginning with a statement of the problem, it describes how cognitive modeling was used to measure the mental workload and work time of controllers running various positions at O’Hare International Airport, both under the current airport configurations and a future set of configurations (proposed in the...

Rapidly advancing modeling technologies, such as data mining algorithms and new modeling languages, are making modeling accessible to an ever-broadening cross-section of knowledge workers. Advances in computer display technologies are also being incorporated into modeling software. Both research and anecdotal evidence suggest that visuals are important in the process of modeling. However, in or...

The design of a “good” business process model is a time-consuming and error-prone task and requests high training effort from the process modeler. These barriers might be a reason why business processes are often designed with software tools, which were not intentionally developed for this purpose, but are highly familiar for the process modeler (e.g., add-ins for MS Office family) and thus a p...