Machine learning methods for commonsense reasoning processes : interactive models /
"The main purpose of this book is to demonstrate the possibility of transforming a large class of machine learning algorithms into integrated commonsense reasoning processes in which inductive and deductive inferences are not separated one from another but moreover they are correlated and suppo...
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| Format: | Electronic |
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Hershey, PA :
Information Science Reference,
2010
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| Online Access: | View fulltext via EzAccess |
Table of Contents:
- Knowledge in the psychology of thinking and mathematics
- Logic-based reasoning in the framework of artiticial intelligence
- The coordination of commonsense reasoning operations
- The logical rules of commonsense reasoning
- The examples of human connonsense reasoning processes
- Machine learning (ML) as a diagnostic task
- The concept of good classification (diagnostic) test
- The duality of good diagnostic tests
- Towards an integrative model of deductive-inductive commonsense reasoning
- Towards a model of fuzzy commonsense reasoning
- Object-oriented technology for expert system generation
- Case technology for psycho-diagnostic system generation
- Commonsense reasoning in intelligent computer systems.