Search Results for author:
Found 8 papers, 3 papers with code
Deep memetic models for combinatorial optimization problems: application to the tool switching problem
In particular, some memetic models can be regarded under this broad interpretation as a group of autonomous basic optimization algorithms that interact among them in a cooperative way in order to deal with a specific optimization problem, aiming to obtain better results than the algorithms that constitute it separately.
Optimizing Hearthstone Agents using an Evolutionary Algorithm
Digital collectible card games are not only a growing part of the video game industry, but also an interesting research area for the field of computational intelligence.
Determining the significance and relative importance of parameters of a simulated quenching algorithm using statistical tools
When search methods are being designed it is very important to know which parameters have the greatest influence on the behaviour and performance of the algorithm.
Metaheuristics "In the Large"
We describe our vision and report on progress, showing how the adoption of common protocols for all metaheuristics can help liberate the potential of the field, easing the exploration of the design space of metaheuristics.
RedDwarfData: a simplified dataset of StarCraft matches
The game Starcraft is one of the most interesting arenas to test new machine learning and computational intelligence techniques; however, StarCraft matches take a long time and creating a good dataset for training can be hard.
NodIO, a JavaScript framework for volunteer-based evolutionary algorithms : first results
We present such an application for running distributed volunteer-based evolutionary algorithm experiments, and we make a series of measurements to establish the speed of JavaScript in evolutionary algorithms that can serve as a baseline for comparison with other distributed computing experiments.
There is no fast lunch: an examination of the running speed of evolutionary algorithms in several languages
It is quite usual when an evolutionary algorithm tool or library uses a language other than C, C++, Java or Matlab that a reviewer or the audience questions its usefulness based on the speed of those other languages, purportedly slower than the aforementioned ones.
Modeling browser-based distributed evolutionary computation systems
From the era of big science we are back to the "do it yourself", where you do not have any money to buy clusters or subscribe to grids but still have algorithms that crave many computing nodes and need them to measure scalability.
