Characteristics of Learning in AI
Learning is done by viewing, listening, interacting, studying, and by experience. It provides us with the power to reason, the ability to handle new situations, and enables us to act intelligently. Human beings are intelligent as they possess knowledge of the world.
Similarly, making a machine intelligent means it should have the power of learning. So, machine learning is a challenge now. An intelligent machine should be able to learn new things and adapt to new situations rather than simply doing steps as they are made to do.
Characteristics of Learning:
The major characteristics of learning are as follows:
1. Rote learning: This learning is by memorization (saving knowledge so that it can be used again).
2. Induction: It involves the process of learning by an example where a system tries to induce a general rule from a set of observed instances.
3. Analogy: It can recognize similarities in information already stored. It can determine the correspondence between two different representations.
4. Genetic Algorithms (GA): It is a part of evolutionary computing. It is a way of solving problems by mimicking processes. Nature uses selection, crosses-over, mutation, and acceptance to evolve a solution to a problem.
5. Reinforcement: It assigns rewards, positive or negative, at the end of a sequence of steps, and it learns which actions are good or bad.