What is machine learning and how has AI become synonymous with ML in the mainstream media? If you refer back to our Venn diagram on the home page of the class, you will note that AI is larger than ML, yet the AI that is in the news is mostly ML.
Machine learning focuses on adaptive methods, or those methods that can adapt the behavior of the agent over time given experience in the environment. The AI methods we have studied so far have not been adaptive. Even when we did replanning (through contingency plans or execution monitoring and replanning), the plan was not adapting to new experiences.
Since there are several full classes at OU on machine learning and since this is an overview class (see the diagram posted in announcements on the week that this module opens to learn more), we will not dive deeply into any of the ML topics but will give an overview of a wide variety of machine learning methods. This module specifically gets us started on what machine learning is and discusses some of the simple ML methods. Later modules will jump more into specific ML methods.
Arthur Samuel, shown on the right, was one of the early pioneers of ML, working to develop a machine learning checkers player in 1955! You can read a short history of his player here. His player was inspirational for many beginning ML. Furthermore, games are a really fun way to get more people interested in AI in the first place – they get involved in playing games and want to make the AI play better!