Add to ORKGIn this paper, we explore the use of genetic algorithms (GAs) to construct a system called GABIL that continually learns and refines concept classification rules from its interaction with the environment. The performance of this system is compared with that of two other concept learners (NEWGEM and C4.5) on a suite of target concepts. From this comparison, we identify strategies responsible for the success of these concept learners. We then implement a subset of these strategies within GABIL to produce a multistrategy concept learner. Finally, this multistrategy concept learner is further enhanced by allowing the GAs to adaptively select the appropriate strategies. Key words: concept learning, genetic algorithms
Concept acquisition is a form of inductive learning that induces general descriptions of concepts fr...
Abstract The problem of concept formation and learning is examined from the viewpoint of granular co...
This book provides a unified framework that describes how genetic learning can be used to design pat...
In this paper, we explore the use of genetic algorithms (GAs) to construct a system called GABIL tha...
In this paper we explore the use of an adaptive search technique (genetic algorithms) to construct a...
In this paper, we explore the use of genetic algorithms (GAs) as a key element in the design and imp...
Genetic Algorithms (GAs) have traditionally been used for non-symbolic learning tasks. In this paper...
Genetic Algorithms (GAs) have traditionally been used for non-symbolic learning tasks. In this chapt...
Summary. This chapter provides a short overview of a GA-based system for in-ductive concept learning...
This paper presents a highly parallel genetic algorithm, designed for concept induction in propositi...
The classical genetic algorithm provides a powerful yet domain-independent tool for concept learning...
In this work the classical learning methods C4.5 [Qui93] and FOIL [Qui90] are compared with the ge-n...
This paper summarizes recent research on competition-based learning procedures performed by the Navy...
Summary. Learning concept descriptions from data is a complex multiobjective task. The model induced...
Abstract: Genetic Algorithm (GA) based concept learner is widely used in supervised learning sys-tem...
Concept acquisition is a form of inductive learning that induces general descriptions of concepts fr...
Abstract The problem of concept formation and learning is examined from the viewpoint of granular co...
This book provides a unified framework that describes how genetic learning can be used to design pat...
In this paper, we explore the use of genetic algorithms (GAs) to construct a system called GABIL tha...
In this paper we explore the use of an adaptive search technique (genetic algorithms) to construct a...
In this paper, we explore the use of genetic algorithms (GAs) as a key element in the design and imp...
Genetic Algorithms (GAs) have traditionally been used for non-symbolic learning tasks. In this paper...
Genetic Algorithms (GAs) have traditionally been used for non-symbolic learning tasks. In this chapt...
Summary. This chapter provides a short overview of a GA-based system for in-ductive concept learning...
This paper presents a highly parallel genetic algorithm, designed for concept induction in propositi...
The classical genetic algorithm provides a powerful yet domain-independent tool for concept learning...
In this work the classical learning methods C4.5 [Qui93] and FOIL [Qui90] are compared with the ge-n...
This paper summarizes recent research on competition-based learning procedures performed by the Navy...
Summary. Learning concept descriptions from data is a complex multiobjective task. The model induced...
Abstract: Genetic Algorithm (GA) based concept learner is widely used in supervised learning sys-tem...
Concept acquisition is a form of inductive learning that induces general descriptions of concepts fr...
Abstract The problem of concept formation and learning is examined from the viewpoint of granular co...
This book provides a unified framework that describes how genetic learning can be used to design pat...