H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 51 Citations 7,360 184 World Ranking 2801 National Ranking 55

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Programming language

His primary scientific interests are in Artificial intelligence, Machine learning, Classifier, Learning classifier system and Evolutionary algorithm. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Fitness function and Pattern recognition. His work in Machine learning tackles topics such as Fuzzy logic which are related to areas like Data analysis and Cluster analysis.

His Classifier study combines topics from a wide range of disciplines, such as Internal memory and Knowledge extraction. The study incorporates disciplines such as Semi-supervised learning, Genetic algorithm, Function approximation and Algorithm in addition to Learning classifier system. His biological study spans a wide range of topics, including Theoretical computer science, Set, Java, Multi-objective optimization and Code coverage.

His most cited work include:

  • An analysis of generalization in the xcs classifier system (319 citations)
  • Mining interesting knowledge from weblogs: a survey (293 citations)
  • Toward a theory of generalization and learning in XCS (200 citations)

What are the main themes of his work throughout his whole career to date?

Pier Luca Lanzi mostly deals with Artificial intelligence, Machine learning, Classifier, Learning classifier system and Evolutionary computation. His Artificial intelligence study combines topics in areas such as Genetic algorithm and Pattern recognition. Pier Luca Lanzi regularly ties together related areas like Process in his Machine learning studies.

His research in Classifier intersects with topics in Algorithm and Classifier. The concepts of his Learning classifier system study are interwoven with issues in Perceptron, Hyper-heuristic, Generalization error and Spiking neural network. His Evolutionary computation research incorporates elements of Theoretical computer science and Computational intelligence.

He most often published in these fields:

  • Artificial intelligence (52.61%)
  • Machine learning (34.35%)
  • Classifier (31.30%)

What were the highlights of his more recent work (between 2013-2021)?

  • Artificial intelligence (52.61%)
  • Rehabilitation (6.96%)
  • Machine learning (34.35%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Rehabilitation, Machine learning, Set and Multimedia. His study in the field of Learning classifier system, Reinforcement learning and Classifier also crosses realms of Structure. His biological study deals with issues like Spiking neural network, which deal with fields such as Temporal logic, Genetic algorithm and Chaining.

His studies in Rehabilitation integrate themes in fields like Phase, Computational intelligence and Adaptation. His work in the fields of Machine learning, such as Active learning, overlaps with other areas such as Multiplexer. His Multimedia research incorporates themes from Evolutionary computation, Evolutionary algorithm and World Wide Web.

Between 2013 and 2021, his most popular works were:

  • Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames (53 citations)
  • Improving reading skills in students with dyslexia: the efficacy of a sublexical training with rhythmic background (33 citations)
  • Intelligent Game Engine for Rehabilitation (IGER) (28 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Programming language

His main research concerns Multimedia, Artificial intelligence, Game design, Rehabilitation and Rhythm. Pier Luca Lanzi combines subjects such as Evolutionary algorithm, Evolutionary computation, World Wide Web and Adaptation with his study of Multimedia. His Artificial intelligence research includes elements of Monte Carlo tree search and State.

His work on Game Developer, Video game development, Game design document and Video game design as part of general Game design research is often related to Screening game, thus linking different fields of science. His research in Video game development intersects with topics in Level design and Video game. The study incorporates disciplines such as Information and Communications Technology, Phase, Virtual machine and Identification in addition to Rehabilitation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Mining interesting knowledge from weblogs: a survey

Federico Michele Facca;Pier Luca Lanzi.
data and knowledge engineering (2005)

480 Citations

An analysis of generalization in the xcs classifier system

Pier Luca Lanzi.
Evolutionary Computation (1999)

320 Citations

Architectures for an Event Notification Service Scalable to Wide-area Networks

Antonio Carzaniga;Luciano Baresi;Gino Biondini;Fabiano Cattaneo.
(2000)

267 Citations

Toward a theory of generalization and learning in XCS

M.V. Butz;T. Kovacs;P.L. Lanzi;S.W. Wilson.
IEEE Transactions on Evolutionary Computation (2004)

260 Citations

Learning Classifier Systems, From Foundations to Applications

Pier Luca Lanzi;Wolfgang Stolzmann;Stewart W. Wilson.
Springer US (2000)

247 Citations

Learning Classifier Systems

Larry Bull;Pier Luca Lanzi;Wolfgang Stolzmann.
soft computing (2002)

222 Citations

Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems

Fabrizio Ferrandi;Pier Luca Lanzi;Christian Pilato;Donatella Sciuto.
networks on chips (2010)

176 Citations

Extending the representation of classifier conditions part I: from binary to messy coding

Pier Luca Lanzi.
genetic and evolutionary computation conference (1999)

154 Citations

What Is a Learning Classifier System

John H. Holland;Lashon B. Booker;Marco Colombetti;Marco Dorigo.
Lecture Notes in Computer Science (2000)

141 Citations

Fast feature selection with genetic algorithms: a filter approach

P.L. Lanzi.
ieee international conference on evolutionary computation (1997)

129 Citations

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Best Scientists Citing Pier Luca Lanzi

Larry Bull

Larry Bull

University of the West of England

Publications: 69

Martin V. Butz

Martin V. Butz

University of Tübingen

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Julian Togelius

Julian Togelius

New York University

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Mengjie Zhang

Mengjie Zhang

Victoria University of Wellington

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Georgios N. Yannakakis

Georgios N. Yannakakis

University of Malta

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Le Hoang Son

Le Hoang Son

Vietnam National University, Hanoi

Publications: 28

Gordon Fraser

Gordon Fraser

University of Passau

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David E. Goldberg

David E. Goldberg

Big Beacon

Publications: 24

Andrea Arcuri

Andrea Arcuri

Campus Kristiania

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Hussein A. Abbass

Hussein A. Abbass

UNSW Sydney

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Francisco Herrera

Francisco Herrera

University of Granada

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Simon M. Lucas

Simon M. Lucas

Queen Mary University of London

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Natalio Krasnogor

Natalio Krasnogor

Newcastle University

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Stewart W. Wilson

Stewart W. Wilson

University of Illinois at Urbana-Champaign

Publications: 12

Risto Miikkulainen

Risto Miikkulainen

The University of Texas at Austin

Publications: 11

Alberto Fernández

Alberto Fernández

University of Granada

Publications: 11

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