Traditional evolution algorithms tend to start the search from scratch. However, real-world
problems seldom exist in isolation and humans effectively manage and execute multiple …

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

Evolutionary computing (EC) is widely used in dealing with combinatorial optimization
problems (COP). Traditional EC methods can only solve a single task in a single run, while …

❑ 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 …

Deep transfer learning has become increasingly prevalent in various fields such as industry
and medical science in recent years. To ensure the successful implementation of target …

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

Traditional evolution algorithms tend to start the search from scratch. However, real-world
problems seldom exist in isolation and humans effectively manage and execute multiple …

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