Jan Treur Livres

Focusing on the complexities of adaptive networks, this book explores their dynamic nature, contrasting them with traditional networks that can be modeled clearly. It highlights how connections in Mental and Social Networks evolve through learning and social interactions, respectively. The text emphasizes the challenges modelers face when integrating procedural specifications for adaptation, leading to a hybrid modeling approach that combines programming elements with traditional modeling techniques. This nuanced perspective aims to enhance understanding and facilitate better modeling practices for adaptive networks.

The 7th volume of the DRUMS Handbook series explores reasoning and dynamics, stemming from the ESPRIT project DRUMS. It focuses on how agents reason about dynamic systems, covering modeling frameworks and formal approaches. The volume combines insights from project researchers and external experts, reflecting on the project's collaborative spirit.

This book introduces a novel approach for addressing complex individual and social human processes, offering an alternative to traditional strategies that rely on isolation and separation. It emphasizes network-oriented modeling, enabling the construction of high-level cognitive, affective, and social models represented as (cyclic) graphs, which can be transformed into executable simulation models. This format allows for the integration of theories and findings related to complex cognitive and social dynamics, often characterized by interrelating cycles. It effectively addresses phenomena such as the interplay of emotions within cognitive processes, internal simulations of others' mental processes, and social dynamics like shared understandings and collective actions. Various sample models demonstrate the approach's potential, covering topics such as ownership of actions, fear, dreaming, emotion integration in joint decision-making, and evolving social networks. Dedicated software supports the creation of models in both conceptual and graphical formats, facilitating their transformation into executable formats for simulation experiments. The material has been positively evaluated by students and researchers in cognitive, social, and AI fields, making it an ideal resource for graduate and undergraduate students across multidisciplinary domains, including cognitive, affective, social, biological, and neuroscience studies.