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Springer Mental Models and Their Dynamics - Springer AI Systems Book

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Description

This comprehensive volume explores how humans employ internal mental models as cognitive blueprints for predicting and preparing for future events through internal simulation. The book presents a generic self-modeling network approach to understanding how mental models are used, adapted, and controlled across various disciplines. Mental models are inherently adaptive-they can be learned, refined, revised, and forgotten as new information and experiences reshape human understanding. This work bridges cognitive science and systems theory, offering insights into the dynamic processes by which people construct, maintain, and modify their internal representations of the world. Part of the Studies in Systems, Decision and Control series (volume 394), it provides both theoretical foundations and practical frameworks for understanding mental model dynamics in artificial intelligence, cognitive science, and decision-making contexts.

Key Features

Springer publication presenting a self-modeling network approach to mental model dynamics and adaptation.

Explores how mental models function as internal blueprints for predicting and simulating future events.

Covers the learning, refinement, revision, and forgetting processes that make mental models adaptive over time.

Part of the Studies in Systems, Decision and Control series, volume 394, addressing systems and decision science.

Integrates perspectives across multiple disciplines including cognitive science, AI, and control theory.

Provides frameworks for understanding how humans use internal simulation to prepare for future scenarios.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
27 January 2022
Listed Since
27 July 2021

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