Janusz Wnek

Constructive Induction-based Learning Agents: An Architecture and Preliminary Experiments (2008)

Eric Bloedorn, Janusz Wnek

This paper introduces a new type of intelligent agent called a constructive induction-based learning agent (CILA). This agent differs from other adaptive agents because it has the ability to not only...

Learning Hybrid Concept Descriptions (2008)

Ryszard S. Michalski, Janusz Wnek

Most symbolic learning methods are concerned with learning concept descriptions in the form of a decision tree or a set of rules expressed in terms of the originally given attributes. For some...

LEARNING DESIGN RULES FOR WIND BRACINGS IN TALL BUILDINGS (2008)

Tomasz Arciszewski, Associate Member Asce, Eric Bloedorn, Ryszard S. Michalski, Mohamad Mustafa, Janusz Wnek

This paper describes a methodology for applying machine learning to problems of conceptual design, and presents a case study of learning design rules for wind bracings in tall buildings. Design rules...

AqBC: A Multistrategy Approach for Constructive Induction (2007)

Seok Won, Janusz Wnek

In order to obtain potentially interesting patterns and relations from large, distributed, heterogeneous databases, it is essential to employ an intelligent and automated KDD (Knowledge Discovery in...

Learning Design Rules For Wind Bracings In Tall Buildings (2007)

Tomasz Arciszewski, Eric Bloedorn, Ryszard S. Michalski, Mohamad Mustafa, Janusz Wnek

This paper describes a methodology for applying machine learning to problems of conceptual design, and presents a case study of learning design rules for wind bracings in tall buildings. Design rules...

American Association for Artificial Intelligence Multistrategy Task-adaptive Learning Using (2007)

Edited Ryszard, S. Michalski, Janusz Wnek, Nabil W. Alkharouf, Ryszard S. Michalski

This research concerns the development of a methodology for representing, plazaflag and executing multitype inferences in a multistrategy task-adaptive learning system. These inferences, defined in...

R.S.,"An Experimental Comparison of Symbolic and Subsymbolic Learning Paradigms: Phase I - Learning Logic-style Concepts (2007)

J. Wnek, R. S. Michalski, Janusz Wnek, Janusz Wnek, Ryszard S. Michalski, Ryszard S. Michalski

The paper discusses and experimentally compares five different methods for concept learning from examples. The first three are symbolic methods, specifically, a decision tree learning method (C4.5),...

BIBLIOGRAPHY OF RECENT MACHINE LEARNING RESEARCH (2007)

Pawel A. Stefanski, Janusz Wnek, Jianping Zhang

This bibliography iS intended to be a useful source of reference for researchers, students and any

COMPARING SYMBOLIC AND SUBSYMBOLIC LEARNING: Three Studies (2007)

G. Tecuci, Morgan Kaumann, Janusz Wnek, Ryszard S. Michalski

This chapter reports on three studies comparing symbolic and subsymbolic methods for concept learning from examples. The first study compared five learning methods, three represenling symbolic...

R.S.,"An Experimental Comparison of Symbolic and Subsymbolic Learning Paradigms: Phase I - Learning Logic-style Concepts (2007)

J. Wnek, R. S. Michalski, Janusz Wnek, Ryszard S. Michalski

ABSTRACT--This paper reports on three studies comparing symbolic and subsymbolic methods for concept learning from examples. The first study compared five learning methods, three representing...

Constructive Induction-based Learning Agents: An Architecture and Preliminary Experiments (2007)

Eric Bloedorn, Janusz Wnek

This paper introduces a new type of intelligent agent called a constructive induction-based learning agent (CILA). This agent differs from other adaptive agents because it has the ability to not only...

Learning Hybrid Concept Descriptions (2007)

Ryszard S. Michalski, Janusz Wnek

Most symbolic learning methods are concerned with learning concept descriptions in the form of a decision tree or a set of rules expressed in terms of the originally given attributes. For some...

Proceedings of the Third International Workshop on Multistrategy Learning, May 23-25 Harpers Ferry, WV. (2003)

Michalski, Ryszard S., Wnek, Janusz

The Third International Workshop on Multistrategy Learning (MSL-96), held in Harpers Ferry, WV, May 23-25, 1996, attracted leading researchers in this area from Australia, Austria, Belgium, France,...

Learning and Revising User Profiles: The Identification of Interesting Web Sites (1997)

Michael Pazzani, Daniel Billsus, S. Michalski, Janusz Wnek

. We discuss algorithms for learning and revising user profiles that can determine which World Wide Web sites on a given topic would be interesting to a user. We describe the use of a naive Bayesian...

A Multistrategy Learning Approach to Flexible Knowledge Organization and Discovery (1997)

Seok Won Lee, Scott Fischthal, Janusz Wnek

Properly organizing knowledge so that it can be managed often requires the acquisition of patterns and relations from large, distributed, heterogeneous databases. The employment of an intelligent and...

Constructive Induction: the Key to Design Creativity (1995)

T. Arciszewski, R. S. Michalski, J. Wnek, Tomasz Arciszews Ki, Ryszard S. Michalski, Janusz Wnek

Abstract. The paper presents initial results from an emerging new direction in engineering design research, in particular, creative design. It argues that constructive induction, which was originally...

Empirical Performance Comparison of Two Symbolic Learning Systems Based on Selective and Constructive Induction (1995)

Witold Szczepanik, Tomasz Arciszewski, Janusz Wnek

The paper provides results of a performance comparison study of two symbolic learning programs, both based on the AQ15C learning algorithm. The first program uses the single representation space...

Constructive Induction: the Key to Design Creativity (1995)

Tomasz Arciszewski, Ryszard S. Michalski, Janusz Wnek

Abstract. The paper presents initial results from an emerging new direction in engineering design research, in particular, creative design. It argues that constructive induction, which was originally...

Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments (1994)

R. Michalski, J. Wnek, J. Wnek, R. S. Michalski, Janusz Wnek, Ryszard S. Michalski

A method for consreactive induction is described that generates new problem-relevant atu'ibutes by analyzing and abstracting iteratively created inductive concept hypotheses. The method, called...

Comparing Symbolic and Subsymbolic Learning (1994)

J. Wnek, J. Wnek, R. S. Michalski, R. S. Michalski, Janusz Wnek, Ryszard S. Michalski

This paper reports on three studies comparing symbolic and subsymbolic methods for concept learning from examples. The first study compared five learning methods, three representing symbolic learning...

Conceptual Transition from Logic to Arithmetic (1994)

Janusz Wnek, Ryszard S. Michalski

This paper presents a computational study of the change of the logic-based concepts to arithmeticbased concepts in inductive learning from examples. Specifically, we address the problem of learning...

A Hypothesis-driven Constructive Induction Approach to Expanding Neural Networks (1994)

Vladimir N. Sazonov, Janusz Wnek

With most machine learning methods, if the given knowledge representation space is inadequate then the learning process will fail. This is also true with methods using neural networks as the form of...

Discovering Representation Space Transformations for Learning Concept Descriptions Combining DNF and M-of-N Rules (1994)

Janusz Wnek, Ryszard S. Michalski

This paper addresses a class of learning problems that require a construction of descriptions that combine both M-of-N rules and traditional Disjunctive Normal form (DNF) rules. The presented method...

Matching Methods with Problems: A Comparative Analysis of Constructive Induction Approaches (1994)

Eric Bloedorn, Ryszard Michalski, Janusz Wnek

This paper provides a taxonomy of constructive induction problems and reports on an empirical comparison of several constructive induction methods. In this paper a representation space is said to be...

Conceptual Transition from Logic to Arithmetic (1994)

Janusz Wnek, Ryszard S. Michalski

This paper presents a computational study of the change of the logic-based concepts to arithmeticbased concepts in inductive learning from examples. Specifically, we address the problem of learning...

The principal axes method for constructive induction (1992)

J. Bala, R. S. Michalski, J. Wnek, Jerzy W. Bala, Ryszard S. Michalski, Janusz Wnek

The paper describes a novel method for consreactive induction, called PRAX (Principal Axes). The madeflying idea of the method is to determine descriptions of a class of certain basic concepts, and...

Comparing Learning Paradigms via Diagrammatic Visualization: A Case Study in Single Concept Learning using Symbolic, Neural Net and Genetic Algorithm Methods (1990)

J. Wnek, J. Sarma, A. Wahab, R. S. Michalski, Study Single, Concept Learning, ...

Four different learning methods are experimentally compared by applying them to a series of simple, single concept learning problems. The methods compared include a rule-learning program, AQI$, a...

Comparing Learning Paradigms via Diagrammatic Visualization: A Case Study in Single Concept Learning using Symbolic, Neural Net and Genetic Algorithm Methods (1990)

J. Wnek, J. Sarma, A. Wahab, R. S. Michalski, Janusz Wnck, Ashraf A. Wahab, ...

Four different learning methods are experimentally compared by applying them to a series of simple, single concept learning problems. The methods compared include a rule-learning program, AQ15, a...