Highlights•Curious robots select actions to maximize intrinsic rewards that quantify learning
progress.•Curious robots exhibit emergence of infant-like exploration behaviors.•Open …

Social interaction is an extremely complex yet vital component in daily life. We present a
bottom-up approach for the emergence of social behaviours from the interaction of the …

In the process of building machine learning models data sometimes must be sampled before
the learning process can be applied. This step, known as instance selection, is mostly done …

Understanding the drivers of invasive species' range expansion is key to effective
management and successful control. Spatial sorting theory advances that invasive species …

When encountering novel environments, animals perform complex yet structured exploratory
behaviors. Despite their typical structuring, the principles underlying exploratory patterns are …

In state-of-the-art big-data applications, the process of building machine learning models
can be very challenging due to continuous changes in data structures and the need for …

Learning to perform household tasks is a key step towards developing cognitive service
robots. This requires that robots are capable of discovering how to use human-designed …

Feature selection (FS) is an important step in the process of building machine learning-
based models. The goal of the FS step is to find a small subset of features that will provide …

In tabular data, certain challenges can negatively affect the quality of machine learning
models, such as high dimensionality, noisy, irrelevant, or repetitive features, interactions …

We discover and examine within a wide phylogenetic perspective spatial neophobia,
avoidance of untrodden terrain, in fruit flies, in an experimental setup that reduces the gap …