International audienceWe investigate how visual analytic tools can deal with the huge amount of data produced during the run of an evolutionary algorithm. We show, on toy examples and on two real life problems, how a multidimensional data visualisation tool like ScatterDice/GraphDice can be easily used for analysing raw output data produced along the run of an evolutionary algorithm. Visual interpretation of population data is not used very often by the EA community for experimental analysis. We show here that this approach may yield additional high level information that is hardly accessible through conventional computation
This paper builds introduces visual-analytic techniques to aggregate, summarize, and visualize the i...
In a previous paper [2], we introduced a number of visualization techniques that we had developed fo...
The success of every stochastic population-based nature-inspired algorithms is characterized through...
International audienceWe investigate how visual analytic tools can deal with the huge amount of data...
International audienceAn experimental analysis of evolutionary algorithms usually generates a huge a...
Experimental analysis of evolutionary algorithms usually aims at tuning the parameter setting or at ...
An experimental analysis of evolutionary algorithms usually gen-erates a huge amount of multidimensi...
Abstract- The non-linear complexity of evolutionary algorithms (EAs) make them a challenge to unders...
International audienceVisualization of large and complex datasets is a research challenge, especiall...
4siWe consider the problem of visualizing the population dynamics along an evolutionary run using a ...
This work assesses the efficacy of evolutionary algorithms (EAs) using an intuitive Multi-Dimensiona...
The comprehension of the Evolutionary Algorithm (EA) search process is often eluded by challenges of...
International audienceRecent publications in the domains of interactive evolution- ary computation a...
Visualization of large and complex datasets is a research challenge, especially in frameworks like i...
This paper builds introduces visual-analytic techniques to aggregate, summarize, and visualize the i...
In a previous paper [2], we introduced a number of visualization techniques that we had developed fo...
The success of every stochastic population-based nature-inspired algorithms is characterized through...
International audienceWe investigate how visual analytic tools can deal with the huge amount of data...
International audienceAn experimental analysis of evolutionary algorithms usually generates a huge a...
Experimental analysis of evolutionary algorithms usually aims at tuning the parameter setting or at ...
An experimental analysis of evolutionary algorithms usually gen-erates a huge amount of multidimensi...
Abstract- The non-linear complexity of evolutionary algorithms (EAs) make them a challenge to unders...
International audienceVisualization of large and complex datasets is a research challenge, especiall...
4siWe consider the problem of visualizing the population dynamics along an evolutionary run using a ...
This work assesses the efficacy of evolutionary algorithms (EAs) using an intuitive Multi-Dimensiona...
The comprehension of the Evolutionary Algorithm (EA) search process is often eluded by challenges of...
International audienceRecent publications in the domains of interactive evolution- ary computation a...
Visualization of large and complex datasets is a research challenge, especially in frameworks like i...
This paper builds introduces visual-analytic techniques to aggregate, summarize, and visualize the i...
In a previous paper [2], we introduced a number of visualization techniques that we had developed fo...
The success of every stochastic population-based nature-inspired algorithms is characterized through...