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Chapter and Conference Paper
Cooperative Co-evolution and Adaptive Team Composition for a Multi-rover Resource Allocation Problem
In this paper, we are interested in ad hoc autonomous agent team composition using cooperative co-evolutionary algorithms (CCEA). In order to accurately capture the individual contribution of team agents, we p...
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Chapter and Conference Paper
Evolutionary Optimisation of Neural Network Models for Fish Collective Behaviours in Mixed Groups of Robots and Zebrafish
Animal and robot social interactions are interesting both for ethological studies and robotics. On the one hand, the robots can be tools and models to analyse animal collective behaviours, on the other hand th...
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Chapter and Conference Paper
How to Blend a Robot Within a Group of Zebrafish: Achieving Social Acceptance Through Real-Time Calibration of a Multi-level Behavioural Model
We have previously shown how to socially integrate a fish robot into a group of zebrafish thanks to biomimetic behavioural models. The models have to be calibrated on experimental data to present correct behav...
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Chapter and Conference Paper
Tutorials at PPSN 2016
PPSN 2016 hosts a total number of 16 tutorials covering a broad range of current research in evolutionary computation. The tutorials range from introductory to advanced and specialized but can all be attended ...
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Chapter and Conference Paper
Environment-Driven Embodied Evolution in a Population of Autonomous Agents
This paper is concerned with a fixed-size population of autonomous agents facing unknown, possibly changing, environments. The motivation is to design an embodied evolutionary algorithm that can cope with the ...
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Chapter and Conference Paper
A Statistical Learning Perspective of Genetic Programming
This paper proposes a theoretical analysis of Genetic Programming (GP) from the perspective of statistical learning theory, a well grounded mathematical toolbox for machine learning. By computing the Vapnik-Ch...
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Chapter and Conference Paper
Unsupervised Learning of Echo State Networks: A Case Study in Artificial Embryogeny
Echo State Networks (ESN) have demonstrated their efficiency in supervised learning of time series: a ”reservoir” of neurons provide a set of dynamical systems that can be linearly combined to match the target...
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Chapter and Conference Paper
Blindbuilder: A New Encoding to Evolve Lego-Like Structures
This paper introduces a new representation for assemblies of small Lego®-like elements: structures are indirectly encoded as construction plans. This representation shows some interesting properties such as hiera...