The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical scien...

Cognitive models represent the knowledge and information processes that are assumed to be required for task performance. Cognitive architectures are used as an integrative framework of psychological theories; they further allow the simulation of human behavior in finegrained steps. The promising potential of cognitive modeling as a method for evaluating dynamic humanmachine systems, especially ...

Although the need to remember to do things in the future is important and ubiquitous in human life, this phenomenon of prospective memory has received little attention in the cognitive modeling community. One roadblock is the lack of a computational definition of the phenomenon. We propose that prospective memory is fundamentally a problem of circular knowledge dependencies. This framework allo...

Rather long ago, Newell (1973) wrote a prophetic paper that could serve as a rallying cry for this 2004 symposium: “You Can’t Play 20 Questions with Nature and Win.” A number of those concerned with integrated cognition know of this paper, which helped catalyze both modern-day computational cognitive modeling through cognitive architectures (like ACT-R, Soar, Polyscheme, CLARION, etc.), and AI’...

The last decade has seen the emergence of a variety of cognitive architectures. This is good news, in general, for cognitive modeling, because architectures provide a readymade set of tools and theoretical constraints that can— according to architectural research methodology—assist the cognitive modeling enterprise by constraining the possible models of a set of phenomena or even making the “ri...

Cognitive robotics is a fascinating field in its own right and comprises both key features of autonomicity and cognitive skills like learning behavior. Cognitive architectures aim at mirroring human memory and assumptions about mental processes. A robot does not only extend the cognitive architecture regarding real-world interaction but brings new and important challenges regarding perception a...

Modeling crowd behavior is an important challenge for cognitive modelers. Models of crowd behavior facilitate analysis and prediction of the behavior of groups of people, who are in close geographical or logical states, and that are affected by each other’s presence and actions. Existing models of crowd behavior, in a variety of fields, leave many open challenges. In particular, psychological m...

Here we discuss the role of modules and representations into cognitive architectures by comparing the “unified” approach of SOAR and ACT-R with the “decentralized” one of the Society of Mind. We introduce AKIRA, an open-source hybrid architecture and show how to exploit its features, namely distributed representations and parallel, concurrent processing for agent based cognitive modeling.

The following introduces CaDaDis, an extension to the architecture-independent VISTA toolkit. CaDaDis creates visible accounts of cognitive model behavior through a set of Categorical Data Displays. It includes a standard Pert Chart showing tasks by category (or resource), a Nonstandard Pert Chart that shows the temporal dependencies, and a Gantt chart that helps show occurrences of agent event...

Based on experimental findings from the study of human cognition we discuss the concept of embodiment for artifacts. We argue that embodiment is linked to a concept of a body and is not necessarily given when running a control program on robot hardware. For this purpose we introduce the concept of ’body image’. Additionally, we stress the individualcharacteristics of an embodied cognitive syste...