Case Technology for Psycho-Diagnostic System Generation

The automated workstation (AWS) for psychologists and physiologists must be an instrument that allows adaptive programming applied psycho-diagnostic expert systems (APDS). For this goal, the AWS must contain toolkits for 1) the automated specification of adaptive psycho-diagnostic systems (APDS) directed by an expert; 2) the adaptation of these systems to changeable conditions of their functioning. We propose an automated technology for creating APDS, the main peculiarity of which consists in using machine learning methods to choose, validate, define and redefine the main constructive elements of psycho-diagnostic testing and decision making procedures utilized in the developed psycho-diagnostic systems.

Commonsense Reasoning in Intelligent Computer Systems

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.

Logic-Based Reasoning in the Framework of Artificial Intelligence

This chapter focuses on the tasks of knowledge engineering related mainly to knowledge acquisition and modeling integrated logic-based inference. We have overlooked the principal and more important directions of researches that pave the ways to understanding and modeling human plausible (commonsense) reasoning in computers.

Towards an Integrative Model of Deductive-Inductive Commonsense Reasoning

The most important steps in the direction to an integrative model of deductive-inductive commonsense reasoning are made in this chapter. The decomposition of inferring good classification tests is advanced into two kinds of subtasks that are in accordance with human mental acts. This decomposition allows modeling incremental inductive-deductive inferences. We give two basic recursive procedures based on two kinds of subtasks for inferring all good maximally redundant classification tests (GMRTs): ASTRA and DIAGaRa. An incremental algorithm INGOMAR for inferring all GMRTs is presented too. The problems of creating an integrative inductive-deductive model of commonsense reasoning are discussed in the last section of this chapter.

The Duality of Good Diagnostic Tests

The concept of good classification test is redefined in this chapter as a dual element of interconnected algebraic lattices. The operations of lattice generation take their interpretations in human mental acts. Inferring the chains of dual lattice elements ordered by the inclusion relation lies in the foundation of generating good classification tests. The concept of an inductive transition from one element of a chain to its nearest element in the lattice is determined. The special reasoning rules for realizing inductive transitions are formed. The concepts of admissible and essential values (objects) are introduced. Searching for admissible or essential values (objects) as a part of reasoning is based on the inductive diagnostic rules. In this chapter, we also propose a non-incremental learning algorithm NIAGaRa based on a reasoning process realizing one of the ways of lattice generation. Next, we discuss the relations between the good test construction and the Formal Concept Analysis (FCA).

Towards a Model of Fuzzy Commonsense Reasoning

This chapter summarizes some methods of inferring approximate diagnostic tests. Considering the sets of approximately minimal diagnostic tests as “characteristic portraits” of object classes we have developed a model of commonsense reasoning by analogy. The system DEFINE of analogical inference with some results of its application is described. Mining approximate functional, implicative dependencies and association rules is based on the same criteria and on applying the same algorithm realized in the Diagnostic Test Machine described shortly in this chapter. Some results of inferring “crisp” and approximate tests with the use of Diagnostic Test Machine are give in Appendix to this chapter.

The Concept of Good Classification (Diagnostic) Test

In this chapter, the definition of good diagnostic test and the characterization of good tests are introduced and the concepts of good maximally redundant and good irredundant tests are given. The algorithms for inferring all kinds of good diagnostic tests are described in detail.

Machine Learning (ML) as a Diagnostic Task

This chapter discusses a revised definition of classification (diagnostic) test. This definition allows considering the problem of inferring classification tests as the task of searching for the best approximations of a given classification on a given set of data. Machine learning methods are reduced to this task. An algebraic model of diagnostic task is brought forward founded upon the partition lattice in which object, class, attribute, value of attribute take their interpretations.

The Examples of Human Commonsense Reasoning Processes

In this chapter, we concentrate our attention on analyzing and modeling natural human reasoning in solving different tasks: pattern recognition in scientific investigations, logical games, and investigation of crimes.

Knowledge in the Psychology of Thinking and Mathematics

This chapter offers a view on the history of developing the concepts of knowledge and human reasoning both in mathematics and psychology. Mathematicians create the formal theories of correct thinking; psychologists study the cognitive mechanisms that underpin knowledge construction and thinking as the most important functions of human existence. They study how the human mind works. The progress in understanding human knowledge and thinking will be undoubtedly related to combining the efforts of scientists in these different disciplines. Believing that it is impossible to study independently the problems of knowledge and human reasoning we strive to cover in this chapter the central ideas of knowledge and logical inference that have been manifested in the works of outstanding thinkers and scientists of past time. These ideas reveal all the difficulties and obstacles on the way to comprehending the human mental processes.