Papers by Federico Divina
Evolutionary computation has been used for optimisation problems since the 1960s, however it is o... more Evolutionary computation has been used for optimisation problems since the 1960s, however it is only recently that these techniques have been used creatively to evolve novel solutions in design or artistic problems. So called creative evolution has, to date, shown impressive results in many areas. This paper describes how, by using these techniques, a flying object can be designed. Our aim in this paper is to show that evolution is capable of exploring the space of possible solutions to a problem providing a range of solutions that are not limited by "conventional wisdom" and "design fixation". In this way entirely new methods and principles for solving a problem can be found and exploited. The results of the experiments indicate that GAs can provide such solutions, which in the context of this paper means novel forms of flying objects.
Lecture Notes in Computer Science, 2006
In this paper we introduce a model for the simulation of language evolution, which is incorporate... more In this paper we introduce a model for the simulation of language evolution, which is incorporated in the New Ties project. The New Ties project aims at evolving a cultural society by integrating evolutionary, individual and social learning in large scale multi-agent simulations. The model presented here introduces a novel implementation of language games, which allows agents to communicate in a more natural way than with most other existing implementations of language games. In particular, we propose a hybrid mechanism that combines cross-situational learning techniques with more informed feedback mechanisms. In our study we focus our attention on dealing with referential indeterminacy after joint attention has been established and on whether the current model can deal with larger populations than previous studies involving cross-situational learning. Simulations show that the proposed model can indeed lead to coherent languages in a quasi realistic world environment with larger populations.
Lecture Notes in Computer Science, 2005
Typically, multi-agent models for studying the evolution of perceptually grounded lexicons assume... more Typically, multi-agent models for studying the evolution of perceptually grounded lexicons assume that agents perceive the same set of objects, and that there is either joint attention, corrective feedback or cross-situational learning. In this paper we address these two assumptions, by introducing a new multi-agent model for the evolution of perceptually grounded lexicons, where agents do not perceive the same set of objects, and where agents receive a cue to focus their attention to objects, thus simulating a Theory of Mind. In addition, we vary the amount of corrective feedback provided to guide learning word-meanings. Results of simulations show that the proposed model is quite robust to the strength of these cues and the amount of feedback received.
Summary. This chapter provides a short overview of a GA-based system for in-ductive concept learn... more Summary. This chapter provides a short overview of a GA-based system for in-ductive concept learning (in a fragment of rst-order logic). The described system exploits problem{speci c knowledge by means of ad-hoc selection, mutation opera-tors and optimization applied to the single individuals. We focus on the experimental analysis of selection operators incorporating problem knowledge.
Lecture Notes in Computer Science, 2003
Non-Universal Suffrage Selection Operators Favor Population Diversity in Genetic Algorithms Feder... more Non-Universal Suffrage Selection Operators Favor Population Diversity in Genetic Algorithms Federico Divina, Maarten Keijzer, Elena Marchiori Vrije Universiteit ... rep-resenting a redundant set of partial solutions, where a chromosome encodes a rule (typically a Horn clause). ...
Studies in Fuzziness and Soft Computing, 2005
This chapter provides a short overview of a GA-based system for inductive concept learning (in a ... more This chapter provides a short overview of a GA-based system for inductive concept learning (in a fragment of first-order logic). The described system exploits problem-specific knowledge by means of ad-hoc selection, mutation operators and optimization applied to the single individuals. We focus on the experimental analysis of selection operators incorporating problem knowledge.
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07, 2007
The main motivation for using a multi-objective evolutionary algorithm for finding biclusters in ... more The main motivation for using a multi-objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters in gene expression matrix, several objectives have to be optimized simultaneously, and often these objectives are in conflict with each other. Moreover, the use of evolutionary computation is justified by the huge dimensionality of the search space, since it is known that evolutionary algorithms have great exploration power.
Protein structure prediction is one of the main challenges in Bioinformatics. An useful represent... more Protein structure prediction is one of the main challenges in Bioinformatics. An useful representation for protein D structure is the protein contact map. In this work, we propose an evolutionary approach for contact map prediction based on amino acids physicochemical properties. The evolutionary algorithm produces a set of rules that identifies contacts between amino acids. The rules obtained by the algorithm imposes a set of conditions on four amino acid properties in order to predict contacts. Results obtained confirm the validity of the proposal.
El objetivo de este artículo es el de presentar tres casos prácticos, en el ámbito de tres asigna... more El objetivo de este artículo es el de presentar tres casos prácticos, en el ámbito de tres asignaturas de la Titulación en Ingeniería Técnica en Informática de Gestión de la Universidad Pablo de Olavide, en los que el trabajo autónomo del alumno ha sido la herramienta utilizada para solventar la problemática provocada por la reducción de horas de clases que deriva de la implantación del EEES que se agravaba más en la modalidad semipresencial de la titulación, modalidad en la que los alumnos, normalmente trabajadores en activo, ven reducidas las horas de presencialidad requerida un 50% para facilitar la compaginación de estudios y actividad laboral. Los resultados obtenidos en términos de tasas de éxito y porcentajes de abandono muestran una mejora de los resultados obtenidos por las asignaturas, corroborando la utilidad de un trabajo autónomo bien planteado.
Evolutionary computation has been used for optimisation problems since the 1960s, however it is o... more Evolutionary computation has been used for optimisation problems since the 1960s, however it is only recently that these techniques have been used creatively to evolve novel solutions in design or artistic problems. So called creative evolution has, to date, shown impressive results in many areas. This paper describes how, by using these techniques, a flying object can be designed. Our aim in this paper is to show that evolution is capable of exploring the space of possible solutions to a problem providing a range of solutions that are not limited by "conventional wisdom" and "design fixation". In this way entirely new methods and principles for solving a problem can be found and exploited. The results of the experiments indicate that GAs can provide such solutions, which in the context of this paper means novel forms of flying objects.
This paper proposes two alternative methods for dealing with numeri- cal attributes in inductive ... more This paper proposes two alternative methods for dealing with numeri- cal attributes in inductive concept learning systems based on genetic algo- rithms. The methods use constraints for restricting the range of values of the attributes and novel stochastic operators for modifying the constraints. These operators exploit information on a subset of thresholds on numer- ical attributes. The methods are embedded
Biclustering techniques aim at extracting significant subsets of genes and conditions from microa... more Biclustering techniques aim at extracting significant subsets of genes and conditions from microarray gene expression data. This kind of algorithms is mainly based on two key aspects: the way in which they deal with gene similarity across the experimental conditions, that determines the quality of biclusters; and the heuristic or search strategy used for exploring the search space. A measure
IEEE Congress on Evolutionary Computation, 2010
AbstractLearning concept descriptions from data is a challenging, and inherently multi-objective... more AbstractLearning concept descriptions from data is a challenging, and inherently multi-objective, optimization pro-blem. The model induced by the learner has to be complete, consistent and easily interpretable, and producing it should take few ...
Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11, 2011
In this paper we propose a novel representation scheme, called probabilistic encoding. In this re... more In this paper we propose a novel representation scheme, called probabilistic encoding. In this representation, each gene of an individual represents the probability that a certain trait of a given problem has to belong to the solution. This allows to deal with uncertainty that can be present in an optimization problem, and grant more exploration capability to an evolutionary algorithm. With this encoding, the search is not restricted to points of the search space. Instead, whole regions are searched, with the aim of individuating a promising region, i.e., a region that contains the optimal solution. This implies that a strategy for searching the individuated region has to be adopted. In this paper we incorporate the probabilistic encoding into a multi-objective and multi-modal evolutionary algorithm. The algorithm returns a promising region, which is then searched by using simulated annealing. We apply our proposal to the problem of discovering biclusters in microarray data. Results confirm the validity of our proposal.
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Papers by Federico Divina