Abstract k-nearest neighbors (k-NN) is a well-known classification algorithm that is widely
used in different domains. Despite its simplicity, effectiveness and robustness, k-NN is …

Abstract Machine learning (ML) offers powerful methods for detecting and modeling
associations often in data with large feature spaces and complex associations. Many useful …

The International Workshop on Learning Classifier Systems (IWLCS) is an annual workshop
at the GECCO conference where new concepts and results regarding learning classifier …

Deforestation, environmental pollution, and the overexploitation of resources, in addition to
the Earth's natural cycles, are scaling up the impacts of climate change in the provision of …

Abstract k-NN is a widely used supervised machine learning method in different domains.
Despite its simplicity, effectiveness, and robustness, k-NN is limited to the use of the …

❑ Rules• A fundamental building block• IF condition THEN action• Generalise relationships
between features in the data and the target endpoint (wildcard/don't care)• Encode input …

When determining the actions to execute, reinforcement learners are constantly faced with
the decision of either exploiting existing knowledge or exploring new options, risking short …

Machine learning (ML) research has yielded powerful tools for training accurate prediction
models despite complex multivariate associations (eg interactions and heterogeneity). In …

On-line learning mechanisms are frequently employed to implement self-adaptivity in
modern systems. With more widespread use in technical systems that interact with their …

Deforestation, environmental pollution, and the overexploitation of resources, in addition to
the Earth's natural cycles, are scaling up the impacts of climate change in the provision of …