This study aims to present a model of learning organization in Islamic Azad University. It is practical in terms of purpose and quantitative in terms of implementation. At the first step of the research, after analyzing the information, using inductive content analysis, 15 components were identified and were categorized into 5 dimensions of learning levels, systematic thinking, shared vis...

OBJECTIVE To analyze the effect of expert knowledge on the inductive learning process in creating classifiers for medical text reports. DESIGN The authors converted medical text reports to a structured form through natural language processing. They then inductively created classifiers for medical text reports using varying degrees and types of expert knowledge and different inductive learning...

approximately correct learning). At the same time, his paper and his subsequent research applied that theoretical framework to analyze the properties of specific machine learning algorithms. At the time of Haussler’s paper, one informal notion popular in machine learning was the “inductive bias” of a learner; that is, the set of assumptions that, together with the training data, logically entai...

We study what kind of data may ease the computational complexity of learning of Horn clause theories (in Gold's paradigm) and Boolean functions (in PAC-learning paradigm). We give several deenitions of good data (basic and generative representative sets), and develop data-driven algorithms that learn faster from good examples, and degenerate to learn in the limit from the \worst" possible examp...

In this paper we propose a use-case-driven iterative design methodology for normative frameworks, also called virtual institutions, which are used to govern open systems. Our computational model represents the normative framework as a logic program under answer set semantics (ASP). By means of an inductive logic programming approach, implemented using ASP, it is possible to synthesise new rules...

In this paper studied are new concepts of robotic behaviors deterministic and quantum probabilistic. In contrast to classical circuits, the quantum circuit can realize both of these behaviors. When applied to a robot, a quantum circuit controller realizes what we call quantum robot behaviors. We use automated methods to synthesize quantum behaviors (circuits) from the examples (examples are car...

The present paper is a short reflection concerning the role which inductive inference played and can play in language learning. We shortly recall some major insights obtained and outline some new directions based on own work and results recently presented in the literature.

PUPS learning mechanisms center around the representation of causal relationships between objects or events. These learning mechanisms involve (1) a set of principles for inducing causal relationships in absence of a domain theory; (2) a set of analogical mechanisms for extrapolating the causal analysis of one situation in order to predict or problem solve in another situation; and (3) compilat...

This paper describes the work on methods for combining rules obtained by machine learning systems. Three methods for obtaining the classification of examples with those rules are compared. The advantages and disadvantages of each method are discussed and the results obtained on three real world domains are commented. The methods compared are: selection of the best rule; PROSPECTOR-like probabil...

Learning by induction can require a large number of training examples. We show the power of using a simulator to generate training data and test data in learning rules for an expert system. The induction program is RL, a simplified version of Meta-DENDRAL. The expert system is ABLE, a rule-based system that identifies and locates errors in particle beam lines used in high energy physics. A simu...