Artificial Evolution
14th International Conference, Évolution Artificielle, EA 2019, Mulhouse, France, October 29–30, 2019, Revised Selected Papers
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Chapter and Conference Paper
Memetic Semantic Genetic Programming for Symbolic Regression
This paper describes a new memetic semantic algorithm for symbolic regression (SR). While memetic computation offers a way to encode domain knowledge into a population-based process, semantic-based algorithms ...
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Chapter and Conference Paper
Multi-objective Genetic Programming for Explainable Reinforcement Learning
Deep reinforcement learning has met noticeable successes recently for a wide range of control problems. However, this is typically based on thousands of weights and non-linearities, making solutions complex, n...
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Chapter and Conference Paper
Multi-resolution Graph Neural Networks for PDE Approximation
Deep Learning algorithms have recently received a growing interest to learn from examples of existing solutions and some accurate approximations of the solution of complex physical problems, in particular rely...
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Book and Conference Proceedings
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Chapter
Algorithm Selector and Prescheduler in the ICON Challenge
Algorithm portfolios are known to offer robust performances, efficiently overcoming the weakness of every single algorithm on some particular problem instances. Two complementary approaches to get the best out...
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Article
An artificial immune system for offline isolated handwritten arabic character recognition
Character recognition plays an important role in the modern world. In recent years, character recognition systems for different languages has gain importance. The recognition of Arabic writing is still an impo...
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Book and Conference Proceedings
Artificial Evolution
13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25–27, 2017, Revised Selected Papers
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Chapter and Conference Paper
On the Use of Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems
In Genetic Programming (GP), the fitness of individuals is normally computed by using a set of fitness cases (FCs). Research on the use of FCs in GP has primarily focused on how to reduce the size of these set...
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Chapter and Conference Paper
Tutorials at PPSN 2018
PPSN 2018 features a total of 23 free tutorials covering a broad range of topics in evolutionary computation and related areas. From theory and methods to applications and computer implementations, and from in...
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Chapter and Conference Paper
Demand-Side Management: Optimising Through Differential Evolution Plug-in Electric Vehicles to Partially Fulfil Load Demand
In this paper, we investigate the use of an stochastic optimisation bio-inspired algorithm, differential evolution, and proposed two fitness (cost) functions that can automatically create an intelligent schedu...
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Book and Conference Proceedings
Artificial Evolution
12th International Conference, Evolution Artificielle, EA 2015, Lyon, France, October 26-28, 2015. Revised Selected Papers
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Chapter and Conference Paper
Anomaly Detection with the Voronoi Diagram Evolutionary Algorithm
This paper presents the Voronoi diagram-based evolutionary algorithm (VorEAl). VorEAl partitions input space in abnormal/normal subsets using Voronoi diagrams. Diagrams are evolved using a multi-objective bio-...
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Chapter and Conference Paper
Feature Based Algorithm Configuration: A Case Study with Differential Evolution
Algorithm Configuration is still an intricate problem especially in the continuous black box optimization domain. This paper empirically investigates the relationship between continuous problem features (measurin...
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Chapter and Conference Paper
On the Use of Semantics in Multi-objective Genetic Programming
Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Mo...
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Chapter and Conference Paper
Greedy Semantic Local Search for Small Solutions
Semantic Backpropagation (SB) was introduced in GP so as to take into account the semantics of a GP tree at all intermediate states of the program execution, i.e., at each node of the tree. The idea is to comp...
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Chapter and Conference Paper
Parameter Setting for Multicore CMA-ES with Large Populations
The goal of this paper is to investigate on the overall performance of CMA-ES, when dealing with a large number of cores — considering the direct map** between cores and individuals — and to empirically find...
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Chapter and Conference Paper
Surrogate Assisted Feature Computation for Continuous Problems
A possible approach to Algorithm Selection and Configuration for continuous black box optimization problems relies on problem features, computed from a set of evaluated sample points. However, the computation ...
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Chapter and Conference Paper
Anti Imitation-Based Policy Learning
The Anti Imitation-based Policy Learning (AIPoL) approach, taking inspiration from the Energy-based learning framework (LeCun et al. 2006), aims at a pseudo-value function such that it induces the same order on t...
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Chapter and Conference Paper
Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve
A method to generate various size tunable benchmarks for multi-objective AI planning with a known Pareto Front has been recently proposed in order to provide a wide range of Pareto Front shapes and different m...
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Chapter
Evolutionary Algorithms
This chapter presents the field of evolutionary algoithms, that is, Darwin-inspired algorithms used to find approximate optimal solutions to some problems, that are not easily, or not all, likely to be reached...
