Artificial-intelligence Feedback
Researchers have developed training-methods for artificial-intelligence devices as well. Evolutionary algorithms, including genetic programming and other methods of machine learning, use a system of feedback based on "fitness functions" to allow computer programs to determine how well an entity performs a task. The methods construct a series of programs, known as a “population” of programs, and then automatically test them for "fitness", observing how well they perform the intended task. The system automatically generates new programs based on members of the population that perform the best. These new members replace programs that perform the worst. The procedure repeats until the achievement of optimum performance. In robotics, such a system can continue to run in real-time after initial training, allowing robots to adapt to new situations and to changes in themselves, for example, due to wear or damage. Researchers have also developed robots that can appear to mimic simple human behavior as a starting point for training.
Read more about this topic: Training, Types of Training