Understanding the population dynamics of an evolutionary algorithm (EA) is very important. It helps us improve the algorithm as well as the optimization process. In this work, we analyzed the diversity of candidate solutions in the evolving population of grammatical…
We have been writing about GELAB in the past. The automatic programming toolbox is quite mature at this stage. Recently we also measured the computational efficiency of the toolbox and we found it on par with the primitive implementation of…
Recently we published an article about the neural correlates of experience. More specifically, the research tries to explore what parts of the brain are activated when a more experienced person engages in an activity as opposed to an inexperienced person.…
Matching the right clients to the right personnel is a key problem in a call center. If they have a nice algorithm that is efficient in this matching job, the call center could save a lot of money and time.…
Matching the right clients to the right personnel is a key problem in a call center. If they have an efficient algorithm that is efficient in this matching job, the call center could save a lot of money and time.…
The efficient market hypothesis (EMH) suggests that a stock market behaves like a random walk which means that developing profitable trading rules and forecasting the trends would be impossible. However, quantitative traders examine the short-term behavior of the market using…
Executive Summary The financial sector has long debated the efficacy of active day trading versus passive “buy and hold” (HODL) strategies. In the volatile cryptocurrency market, traditional time-series forecasting often fails to account for non-linear market dynamics. This case study…
We have been publishing about grammatical evolution in quite a lot of detail in the past. Here is another one. In this work, we have developed the ability to evolve multi-input multi-output neural networks using grammatical evolution. The main target…
Recently we released Blizzard. It is capable of doing hybrid optimization using GELAB. Hybrid optimization is an important family of learning algorithms. Its main benefit in plain words is that it is helpful for training machines to perform intricate tasks.…
Recently we have been involved in developing controllers for simulated racing cars. Our work was published at a renowned conference. The controllers we propose were derived using Artificial Neural Networks (ANNs). Our work is a forerunner in the niche of…