Commonsense Reasoning in Intelligent Computer Systems

Commonsense Reasoning in Intelligent Computer Systems

Xenia Naidenova (Military Medical Academy, Russia)
DOI: 10.4018/978-1-60566-810-9.ch013
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Abstract

This chapter deals with the description of possible mechanisms for data-knowledge organization and management in intelligent computer systems. Challenges and future trends will be discussed in the last section of this chapter, followed by the concluding remarks.
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Introduction

We shall consider the intelligent computer system as a system capable to commonsense reasoning. The database system is intelligent if it communicates with the users by means of commonsense reasoning on conceptual knowledge rather than by means of special formal query languages. In this chapter, we attempt to formulate the main principles which could be posed in the foundation of constructing intelligent computer database systems first of all.

Furthermore, we shall examine the basic difficulties of commonsense reasoning realization in computers both from the side of the organization of data-knowledge interaction and from the side of the realization of machine learning.

These difficulties are connected with the solution of the following four problems:

  • Data-knowledge interaction;

  • Representation or structural organization of data and knowledge;

  • Integration of conceptual clustering and supervised conceptual machine learning, in which, for interpreting objects’ classifications, it is drawn the knowledge of intelligent system instead of the knowledge of a supervisor;

  • Procedural analysis and synthesis (genesis) of objects from elementary components.

Certainly, we cannot give the comprehensive solution of these problems. Our modest task is intended for formulating the main directions of future studies for their solution.

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Integration Of Data And Knowledge

The integration of data and knowledge is an important constituent of the integration of all type of reasoning in intelligent computer systems. Probably the solution of one of these problems draws the solution of another. We consider some ideas of interaction between data and knowledge.

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