Dynamics, Adaptation and Control for Mental Models: A Cognitive Architecture -- Bringing Networks to the Next Level: Self-Modeling Networks for Adaptivity and Control of Mental Models -- On Becoming a Good Driver: Modeling the Learning of a Mental Model -- Controlling Your Mental Models: Using Metacognition to Control Use and Adaptation for Multiple Mental Models -- Disturbed by Flashbacks: a Controlled Adaptive Network Model Addressing Mental Models for Flashbacks from PTSD.

This book introduces a generic approach to model the use and adaptation of mental models, including the control over this. In their mental processes, humans often make use of internal mental models as a kind of blueprints for processes that can take place in the world or in other persons. By internal mental simulation of such a mental model in their brain, they can predict and be prepared for what can happen in the future. Usually, mental models are adaptive: they can be learned, refined, revised, or forgotten, for example. Although there is a huge literature on mental models in various disciplines, a systematic account of how to model them computationally in a transparent manner is lacking. This approach allows for computational modeling of humans using mental models without a need for any algorithmic or programming skills, allowing for focus on the process of conceptualizing, modeling, and simulating complex, real-world mental processes and behaviors. The book is suitable for and is used as course material for multidisciplinary Master and Ph.D. students.