Schema Satisfaction Reasoning and Its Applications

Schema Satisfaction Reasoning and Its Applications

Kambiz Badie (Knowledge Management & e-Organizations Group, IT Research Faculty, ICT Research Institute, Iran)
DOI: 10.4018/978-1-4666-5888-2.ch109
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Background

The point which is emphasized in this section is the role of constraint satisfaction networks in problem solving and optimization issues.

Key Terms in this Chapter

Common Sense Reasoning: The process of reasoning based on common (and not specific) knowledge such as defaults and general beliefs.

Schema: A chunk of the information with certain configuration that can participate in memorizing issues for problem solving and decision-making purposes.

Hopfield Network: A connectionist network proposed by John Hopfield using Hebbian learning rule and suitable for a wide range of association, identification, recognition, … type problems.

Schema Satisfaction Reasoning: The process of reasoning with the purpose of satisfying schemas as constraints.

Extracting Focal Points: The process of extracting points from a text (or an image), which can be considered as the focus of attention for the observer.

Justification: The process of demonstrating how a fact can be true, valid or consistent.

Emotion Adjustment: The process of transformation in one’s emotional state based on sensed & perceived facts.

Constraint Satisfaction Network: A computational perspective on the function of the network for satisfying constraints from the environmental inputs in a simultaneous way.

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