Discovering the different types of learning processes

Learning is based on the idea that perceptions should not only guide actions but also enhance the agent’s ability to automatically learn from interactions with the world and the decision-making processes themselves. A system is considered capable of learning when it has an executive component for making decisions and a learning component for modifying the executive component to improve decisions. Learning is influenced by the components learned from the system, by the feedback received after the actions are performed, and by the type of representation used.

ML offers several ways of allowing algorithms to learn from data, which are classified into categories based on the type of feedback on which the learning system is based. Choosing which learning category to use for a specific problem must be done in advance to find the best solution. It is useful to evaluate the robustness of the algorithm, such as its ability to make...