The International Workshop on Learning Classifier Systems (IWLCS) is a yearly workshop at
the GECCO conference where new concepts and results all around Learning Classifier …

Artificial intelligence based autonomous systems interacting with dynamic environment are
required to continuously learn, accumulate and improve the learned knowledge. Currently …

Deep learning has achieved a high classification accuracy on image classification tasks,
including emotion categorization. However, deep learning models are highly vulnerable to …

Human intelligence can simultaneously process many tasks with the ability to accumulate
and reuse knowledge. Recent advances in artificial intelligence, such as transfer, multitask …

Multitask Learning is a learning paradigm that deals with multiple different tasks in parallel
and transfers knowledge among them. XOF, a Learning Classifier System using tree-based …

Emotion categorization has become an increasingly important area of research due to the
rising number of intelligent systems. Artificial classifiers have demonstrated limited …

Evolutionary Computation (EC) often throws away learned knowledge as it is reset for each
new problem addressed. Conversely, humans can learn from small-scale problems, retain …

A major goal of machine learning is to create techniques that abstract away irrelevant
information. The generalisation property of standard Learning Classifier Systems (LCSs) …

Deep learning has achieved a high classification accuracy on image classification tasks,
including emotion categorization. However, deep learning models are highly vulnerable to …