Deep Mind’s Alpha Go, the Go-playing engine that defeated the World Go Champion Lee Sedol in March 2016, is one of the biggest achievements of Artificial Intelligence.
In a nutshell, Alpha Go is a decision-making agent that takes decisions in an uncertain environment, exploring the potential consequences of their own choices using complex estimates of the world around.
This course is a study of the basic building blocks of decision-making agents, which are abstract entities living in an uncertain environment and are guided towards the realisation of given objectives.
An agent is typically endowed with a knowledge base, a collection of facts expressed in some logical language, and an action repertoire at each state. The agent can reason about the environment, using their knowledge base, and take decisions accordingly. The environment is typically unknown, stochastic, and evolves following some rules that might be unknown to the agent, as well. On top of this, it is usually inhabited by other agents, which may or may not strive to achieve similar objectives. The task is to take the best possible decision that can be taken given the (incomplete) information available.
This simple model is the basis of a number of important achievements in AI, and combines the use of logical, game-theoretic and algorithmic analysis.
You do not need any prior knowledge of these fields to study this course and it is open to anyone.