Introduction to Artificial Intelligence
Computers are not just better than us at memory or calculation. They are better than us at a poker table.
Practical information:
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In December 2017, Carnegie Mellon poker playing computer Libratus has stunned the world by winning 1.7M in a 20 days tournament against four poker stars.
In a nutshell, Libratus 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.
“ The artificial intelligence course was incredibly motivating. Learning from the teachers with other students from across the globe was an absolute pleasure and the classes encouraged me to be passionate about the subject, making me want to learn more. ”
Teachers / speakers
Associate Professor in Computer Science, University of Warwick.
I am interested in Artificial Intelligence for social good. In my work I use game theory to design artificial agents and environments that display desirable social behaviour.
Charlie Pilgrim is now a Research Fellow at the University of Leeds. He is interested in understanding how humans communicate with each other and how that affects our beliefs, behaviour and outcomes. His research includes elements of agent-based modelling, information theory, Bayesian networks, social science, psychology, evolution and data science.
