Journal

An analysis of the ingredients for learning interpretable symbolic regression models with human-in-the-loop and genetic programming

Interpretability is a critical aspect to ensure a fair and responsible use of machine learning (ML) in high-stakes applications. Genetic programming (GP) has been used to obtain interpretable ML models because it operates at the level of functional …

Discovering Non-Linear Boolean Functions by Evolving Walsh Transforms with Genetic Programming

Stream ciphers usually rely on highly secure Boolean functions to ensure safe communication within unsafe channels. However, discovering secure Boolean functions is a non-trivial optimization problem that has been addressed by many optimization …

Mouse Sensitivity in First-Person Targeting Tasks

Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. …

Revisiting of AlphaStar

Research on StarCraft II (SC2) is considered important due to its similarity to real-life tasks and its potential to inspire game artificial intelligence design. However, the complexity of SC2 presents considerable challenges. In 2019, DeepMind …

An evolutionary computation approach for twitter bot detection

Bot accounts are automated software programs that act as legitimate human profiles on social networks. Identifying these kinds of accounts is a challenging problem due to the high variety and heterogeneity that bot accounts exhibit. In this work, we …

Trajectory clustering for air traffic categorisation

Availability of different types of data and advances in data-driven techniques open the path to more detailed analyses of various phenomena. Here, we examine the insights that can be gained through the analysis of historical flight trajectories, …

Generative adversarial networks for generating synthetic features for Wi-Fi signal quality

Wireless networks are among the fundamental technologies used to connect people. Considering the constant advancements in the field, telecommunication operators must guarantee a high-quality service to keep their customer portfolio. To ensure this …

Creating Pro-Level AI for a Real-Time Fighting Game Using Deep Reinforcement Learning

Reinforcement learning (RL) combined with deep neural networks has performed remarkably well in many genres of games recently. It has surpassed human-level performance in fixed game environments and turn-based two-player board games. However, to the …

Machine learning techniques for hate speech classification of twitter: data State-of-the-art, future challenges and research directions

Twitter is a microblogging tool that allow the creation of big data through short digital contents. This study provides a survey of machine learning techniques for hate speech classification from Twitter data streams. Hate speech classification in …

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. This game genre allows researchers to deal with hidden information, uncertainty …