Recent research in psychology and neuroscience has identified both the critical role of emotion in decision-making and social interaction, and some of the mechanisms mediating the functioning of emotion. Yet the majority of cognitive architectures do not include models of emotion. In this paper I first motivate the need for including emotion in cognitive architectures, and then describe a gener...

In this short paper, we argue that there are two conflicting agendas at play in the design of cognitive architectures. One is principled: to create a model of cognition and gain an understanding of cognitive processes. The other is practical: to build useful systems that have a cognitive ability and thereby provide robust adaptive behaviour that can anticipate events and the need for action. Th...

A remarkable property of human cognition is the systematic co-occurrence of certain cognitive abilities. One challenge for cognitive science is to determine the (computational) principles that derive this property as part of a broader goal of establishing the foundations of cognitive architecture (i.e. the basic processes and modes of combination affording cognitive capacity) for a science of c...

Cognitive scientists must understand not just what the mind does, but how it does what it does. In this paper, I consider four aspects of cognitive architecture: how the mind develops, the extent to which it is or is not modular, the extent to which it is or is not optimal, and the extent to which it should or should not be considered a symbol-manipulating device (as opposed to, say, an elimina...

We present a task-independent learning procedure which produces gradual performance improvement through experience on a perceptual-motor ask. It utilizes a data structure that represents a strategy for performing the task. This learning procedure is a direct result of the constraints that occur when realistic perceptual and motor mechanisms (EPIC) are mated to a learning cognitive modeling arch...

This paper reviews three hybrid cognitive architectures (Soar, ACT-R, and CoJACK) and how they can support including models of emotions. There remain problems creating models in these architectures, which itself remains a research and engineering problem. Thus, the term cognitive science engineering is introduced as an area that would support making models easier to create, understand, and re-use.

Systematicity commonly means that having certain cognitive capacities entails having certain other cognitive capacities. Learning is a cognitive capacity central to cognitive science, but systematic learning of cognitive capacities—second-order systematicity—has received little investigation. We proposed associative learning as an instance of second-order systematicity that poses a paradox for ...

We describe an improved version of the Able cognitive model that exhibits a novice to expert transition in solving physics problems. The initial model was written by Larkin and initially translated into Soar (ver. 4) by Levy. In revising it to run in the latest version of Soar (7.0.4), we have updated it to be an exemplar of an understandable and reusable cognitive model. It includes graphic di...

When it comes to decision making, the dominant view suggests that engaging in a detailed analytical thought process is more beneficial than deciding based on one’s feelings. However, there seems to be a tradeoff, as the complexity and amount of elements on which to base the decision increases, decisions based on affect seem to be more accurate than decisions based on a thorough analytical proce...