"Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)" - Information and Links:

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The cover of “Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)” - Open Library.

"Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)" is published by Springer in September 25, 2002, it has 360 pages and the language of the book is English.


“Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)” Metadata:

  • Title: ➤  Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)
  • Author:
  • Language: English
  • Number of Pages: 360
  • Publisher: Springer
  • Publish Date:

“Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)” Subjects and Themes:

Edition Specifications:

  • Format: Paperback
  • Weight: 1.4 pounds
  • Dimensions: 9 x 6.2 x 0.8 inches

Edition Identifiers:

AI-generated Review of “Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)”:


Snippets and Summary:

Recently there has been a significant amount of interest in a new and growing area of research referred to as diagrammatic or visual reasoning.

"Logical and Computational Aspects of Model-Based Reasoning (APPLIED LOGIC SERIES Volume 25) (Applied Logic Series)" Description:

The Open Library:

The study of diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of traditional notions of reasoning such as classical logic. Understanding the contribution of modeling practices to discovery and conceptual change in science requires expanding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philosophy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model-based reasoning. The term 'model' comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. Moreover, in the modeling process, various forms of abstraction are used. Evaluation and adaptation take place in light of structural, causal, and/or functional constraints. Model simulation can be used to produce new states and enable evaluation of behaviors and other factors.

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