We live in the age of complexity. Yet, complexity is rarely studied in MIS. The paper studies cognitive complexity in an important IS domain – data modeling. The focus is on novice data modelers. Four major sources of complexity principles are identified: problem solving principles, design principles, information overload, and systems theory. Based on prior literature, the factors that lead to ...

This paper presents a computational approach to intelligence analysis which is viewed as ceaseless discovery in a non-stationary world involving concurrent processes of evidence in search of hypotheses, hypothesis in search of evidence, and evidential tests of hypotheses. This approach is at the basis of Disciple-LTA, a cognitive assistant that helps intelligence analysts evaluate the likelihoo...

In the last twenty years an important effort in brain sciences, especially in cognitive science, has been the development of mathematical tool that can deal with the complexity of extensive recordings corresponding to the neuronal activity obtained from hundreds of neurons. We discuss here along with some historical issues, advantages and limitations of Artificial Neural Networks (ANN) that can...

Although (business) process models are frequently used to promote human understanding of processes, practice shows that understanding complex models soon reach cognitive limits. The aim of this paper is to investigate the cognitive difficulty of understanding different relations between model elements. To allow for empirical assessment of this research question we systematically constructed mod...

Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity...

This chapter surveys the use of logic and computational complexity theory in cognitive science. We emphasize in particular the role played by logic in bridging the gaps between Marr’s three levels: representation theorems for non-monotonic logics resolve algorithmic/implementation debates, while complexity theory probes the relationship between computational task analysis and algorithms. We arg...

The Brahms Generalized Überlingen Model (Brahms-GÜM) is a cognitive-behavioral simulation of aviation work practices that reveals how normally complicated situations become cognitively complex for people in a dynamic environment of malfunctioning tools and non-routine workload. Brahms-GÜM was developed by analyzing and generalizing the roles, systems, and events leading to an aircraft collision...

Knowledge can be specified at different levels of conceptualisation or abstraction. In this paper, lessons learned on the philosophical foundations of cognitive science are discussed, with a focus on how the relationships of cognitive theories with specific underlying (physical/biological) makeups can be dealt with. It is discussed how these results can be applied to relate different types of k...

In this work we present a simulation study drawn upon a famous ethological example: food-sharing habit of vampire bats in Central America. A norm of reciprocity is introduced when agents are expected to exhibit a cooperative behavior under serious environmental strictures (infrequent but lethal food scarcity). We compare different agents’ architectures (with different levels of cognitive comple...

Based on previous studies that cognitive complexity and coping flexibility are closely related with psychological adaptibility, it can be inferred that they can influence management ability of countertransference in counselling. This study focused on the influence of counselor's cognitive complexity and coping flexibility on the management ability of countertransference in counselling. The surv...