IWLCS 2009 review
[Aug 6, 2009 | No Comment | Posted by Jaume Bacardit ]
IWLCS 2009 review

By Will Browne, Jan Drugowitsch and Jaume Bacardit
The 12th International Workshop on Learning Classifier Systems (LCS) successfully took place on July 9th, 2009 in Montreal, Canada as part of GECCO 09. Its ’success’ was measured in terms of number of attendees – multiple times the number of presenters, quality of papers, diversity of topics, originality [...]

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GPEM 10(4) now available online
[Nov 6, 2009 | Comments Off | Posted by Community ]

The fourth issue of volume 10 of Genetic Programming and Evolvable Machines is now available online. This is the first part of the two-part Special Issue on Parallel and Distributed Evolutionary Algorithms, and it contains the following articles:

Introduction: special issue on parallel and distributed evolutionary algorithms, part I
by Marco Tomassini & Leonardo Vanneschi
Distributed differential evolution with explorative–exploitative population families
by Matthieu Weber, Ferrante Neri & Ville Tirronen
A grid-enabled asynchronous metamodel-assisted evolutionary algorithm for aerodynamic optimization
by V. G. Asouti, I. C. Kampolis & K. C. Giannakoglou
Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework
by Asim Munawar, Mohamed Wahib, Masaharu Munetomo & Kiyoshi Akama
Parallel evolution using multi-chromosome cartesian genetic programming
by James Alfred Walker, Katharina Völk, Stephen L. Smith & Julian Francis Miller
Genetic programming on graphics processing units
by Denis Robilliard, Virginie Marion-Poty & Cyril Fonlupt
Book Review: Natalio Krasnogor, Steve Gustafson, David A. Pelta, and Jose L. Verdegay (eds): Systems self-assembly: multidisciplinary snapshots
by Navneet Bhalla

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Design e Sviluppo di Videogiochi: UBISOFT al Politecnico di Milano 5 Novembre ore 13:00
[Nov 3, 2009 | Comments Off | Posted by Pier Luca Lanzi ]

Giovedi’ 5 Novembre 2009 alle ore 1300, presso l’Educafe’, Chiostro Edificio Nord, il producer di Ubisoft, una delle industrie leader nel settore dei videogiochi, terra’ una presentazione intitolata:
“Opportunità di lavoro in Ubisoft: dai forma all’industria dell’intrattenimento di oggi e domani”
L’incontro della durata di 45 minuti circa vertera’ sui seguenti
argomenti:

Presentazione Ubisoft e Studios di Milano

Il processo [...]

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Evolving Drivers for TORCS using On-Line Neuroevolution
[Nov 2, 2009 | Comments Off | Posted by Community ]

We applied on-line neuroevolution to evolve non-player characters for
The Open Racing Car Simulator. While previous approaches allowed on-line
learning with performance improvements during each generation,
our approach enables a finer grained on-line learning with performance
improvements within each lap. We tested our approach on three tracks
using two methods of on-line neuroevolution (NEAT and rtNEAT) combined
with four evaluation strategies [...]

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Numerical simplification for bloat control and analysis of building blocks in genetic programming
[Nov 2, 2009 | Comments Off | Posted by Community ]

Abstract  In tree-based genetic programming, there is a tendency for the size of the programs to increase from generation to generation,
a phenomenon known as bloat. It is standard practice to place some form of control on program size either by limiting the
number of nodes or the depth of the program trees, or by adding a component to the fitness function that rewards smaller programs
(parsimony pressure). Others have proposed directly simplifying individual programs using algebraic methods. In this paper,
we add node-based numerical simplification as a tree pruning criterion to control program size. We investigate the effect
of on-line program simplification, both algebraic and numerical, on program size and resource usage. We also investigate the
distribution of building blocks within a genetic programming population and how this is changed by using simplification. We
show that simplification results in reductions in expected program size, memory use and computation time. We also show that
numerical simplification performs at least as well as algebraic simplification, and in some cases will outperform algebraic
simplification. We further show that although the two on-line simplification methods destroy some existing building blocks,
they effectively generate new more diverse building blocks during evolution, which compensates for the negative effect of
disruption of building blocks.

  • Content Type Journal Article
  • Category Special Issue
  • DOI 10.1007/s12065-009-0029-9
  • Authors
    • David Kinzett, Victoria University of Wellington School of Engineering and Computer Science PO Box 600 Wellington New Zealand
    • Mark Johnston, Victoria University of Wellington School of Mathematics, Statistics and Operations Research PO Box 600 Wellington New Zealand
    • Mengjie Zhang, Victoria University of Wellington School of Engineering and Computer Science PO Box 600 Wellington New Zealand

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Improving the performance of evolutionary algorithms in grid-based puzzles resolution
[Oct 31, 2009 | Comments Off | Posted by Community ]

Abstract  This paper proposes several modifications to existing hybrid evolutionary algorithms in grid-based puzzles, using a-priori
probabilities of 0/1 occurrence in binary encodings. This calculation of a-priori probabilities of bits is possible in grid-based
problems (puzzles in this case) due to their special structure, with the solution confined into a grid. The work is focused
in two different grid-based puzzles, the Japanese puzzles and the Light-up puzzle, each one having special characteristics
in terms of constraints, which must be taken into account for the probabilities of bit calculation. For these puzzles, we
show the process of a-priori probabilities calculation, and we modify the initialization of the EAs to improve their performance.
We also include novel mutation operators based on a-priori probabilities, which makes more effective the evolutionary search
of the algorithms in the tackled puzzles. The performance of the algorithms with these new initialization and novel mutation
operators is compared with the performance without them. We show that the new initialization and operators based on a-priori
probabilities of bits make the evolutionary search more effective and also improve the scalability of the algorithms.

  • Content Type Journal Article
  • Category Special Issue
  • DOI 10.1007/s12065-009-0030-3
  • Authors
    • E. G. Ortiz-García, Universidad de Alcalá, Escuela Politécnica Superior Department of Signal Theory and Communications Alcalá de Henares 28871 Madrid Spain
    • S. Salcedo-Sanz, Universidad de Alcalá, Escuela Politécnica Superior Department of Signal Theory and Communications Alcalá de Henares 28871 Madrid Spain
    • Á. M. Pérez-Bellido, Universidad de Alcalá, Escuela Politécnica Superior Department of Signal Theory and Communications Alcalá de Henares 28871 Madrid Spain
    • L. Carro-Calvo, Universidad de Alcalá, Escuela Politécnica Superior Department of Signal Theory and Communications Alcalá de Henares 28871 Madrid Spain
    • A. Portilla-Figueras, Universidad de Alcalá, Escuela Politécnica Superior Department of Signal Theory and Communications Alcalá de Henares 28871 Madrid Spain
    • X. Yao, The University of Birmingham The Centre for Research in Computational Intelligence and Applications (CERCIA), School of Computer Science Birmingham UK

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Evolutionary synthesis of low-sensitivity digital filters using adjacency matrix
[Oct 24, 2009 | Comments Off | Posted by Community ]

Abstract  An evolutionary synthesis method to generate digital filters with low coefficient sensitivity is presented. The method uses
a chromosome coding based on the graph adjacency matrix representation. It is shown that the proposed chromosome representation
enables to easily verify and avoid the generation of topologically invalid and non-computable individuals during the evolutionary
process. The efficiency of the proposed algorithm is tested in the synthesis of two low-pass digital filters and the results
are compared with other examples found in the literature.

  • Content Type Journal Article
  • Category Research Paper
  • DOI 10.1007/s12065-009-0028-x
  • Authors
    • Leonardo Bruno de Sá, Brazilian Army Technological Center Av das Américas, 28705, Guaratiba Rio de Janeiro 23020-470 Brazil
    • Antonio Mesquita, Federal University of Rio de Janeiro Rio de Janeiro Brazil

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Rule base and adaptive fuzzy operators cooperative learning of Mamdani fuzzy systems with multi-objective genetic algorithms
[Oct 24, 2009 | Comments Off | Posted by Community ]

Abstract  In this paper, we present an evolutionary multi-objective learning model achieving cooperation between the rule base and the
adaptive fuzzy operators of the inference system in order to obtain simpler, more compact and still accurate linguistic fuzzy
models by learning fuzzy inference adaptive operators together with rules. The multi-objective evolutionary algorithm proposed
generates a set of fuzzy rule based systems with different trade-offs between interpretability and accuracy, allowing the
designers to select the one that involves the most suitable balance for the desired application. We develop an experimental
study testing our approach with some variants on nine real-world regression datasets finding the advantages of cooperative
compared to sequential models, as well as multi-objective compared with single-objective models. The study is elaborated comparing
different approaches by applying non-parametric statistical tests for pair-wise. Results confirm the usefulness of the proposed
approach.

  • Content Type Journal Article
  • Category Special Issue
  • DOI 10.1007/s12065-009-0026-z
  • Authors
    • Antonio A. Márquez, University of Huelva Information Technologies Department Huelva Spain
    • Francisco A. Márquez, University of Huelva Information Technologies Department Huelva Spain
    • Antonio Peregrín, University of Huelva Information Technologies Department Huelva Spain

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Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets
[Oct 24, 2009 | Comments Off | Posted by Community ]

Abstract  Exploiting the information in low quality datasets has been recently acknowledged as a new challenge in Genetic Fuzzy Systems.
Owing to this, in this paper we discuss the basic principles that govern the extension of a fuzzy rule based classifier to
interval and fuzzy data. We have also applied these principles to the genetic learning of a simple cooperative-competitive
algorithm, that becomes the first example of a Genetic Fuzzy Classifier able to use low quality data. Additionally, we introduce
a benchmark, comprising some synthetic samples and two real-world problems that involve interval and fuzzy-valued data, that
can be used to assess future algorithms of the same kind.

  • Content Type Journal Article
  • Category Special Issue
  • DOI 10.1007/s12065-009-0024-1
  • Authors
    • Ana M. Palacios, Universidad de Oviedo Departamento de Informática 33071 Gijón Asturias Spain
    • Luciano Sánchez, Universidad de Oviedo Departamento de Informática 33071 Gijón Asturias Spain
    • Inés Couso, Universidad de Oviedo Departamento de Estadística e I.O. y D.M 33071 Gijón Asturias Spain

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Evolution of visual controllers for obstacle avoidance in mobile robotics
[Oct 23, 2009 | Comments Off | Posted by Community ]

Abstract  The purpose of this work is to automatically design vision algorithms for a mobile robot, adapted to its current visual context.
In this paper we address the particular task of obstacle avoidance using monocular vision. Starting from a set of primitives
composed of the different techniques found in the literature, we propose a generic structure to represent the algorithms,
using standard resolution video sequences as an input, and velocity commands to control a wheel robot as an output. Grammar
rules are then used to construct correct instances of algorithms, that are then evaluated using different protocols: evaluation
of trajectories performed in a goal reaching task, or imitation of a hand-guided trajectory. A genetic program is applied
to evolve populations of algorithms in order to optimize the performances of the controllers. The first results obtained in
a simulated environment show that the evolution produces algorithms that can be easily interpreted and which are clearly adapted
to the visual context. However, the resulting trajectories are often erratic, and the generalization capacities are poor.
To improve the results, we propose to use a two-phase evolution combining imitation and goal reaching evaluations, and to
add some constraints in the grammar rules to enforce a more generic behavior. The results obtained in simulation show that
the evolved algorithms are more efficient and more generic. Finally, we apply the imitation based evolution on real sequences
and test the evolved algorithms on a real robot. Though simplified by dropping the goal reaching constraint, the resulting
algorithms behave well in a corridor centering task, and show certain generalization capacities.

  • Content Type Journal Article
  • Category Research Paper
  • DOI 10.1007/s12065-009-0021-4
  • Authors
    • Renaud Barate, ENSTA 32 Bd Victor 75739 Paris Cedex 15 France
    • Antoine Manzanera, ENSTA 32 Bd Victor 75739 Paris Cedex 15 France

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