The notion of an (intelligent) agent is fundamental to the field of artificial intelligence. Thereby an agent is viewed as a computational entity such as a software program or a robot that is situated in some environment and that to some extent is able to act autonomously in order to achieve its design objectives. The course covers important conceptual, theoretical and practical foundations of single-agent systems (where the focus is on agent-environment interaction) and multi-agent systems (where the focus is on agent-agent interaction). Both types of agent-based systems have found their way to real-world applications in a variety of domains such as e-commerce, logistics, supply chain management, telecommunication, health care, and manufacturing. Examples of topics treated in the course are agent architectures, computational autonomy, game-theoretic principles of agent-based systems, coordination mechanisms (including auctions and voting), and automated negotiation and argumentation. Other topics such as ethical or legal aspects raised by computational agency may also be covered. In the exercises and in the practical part of the course students have the opportunity to apply the covered concepts and methods.
Prerequisites
Desired Prior Knowledge: Basic knowledge and skills in programming.
Recommended reading
Stuart Russell and Peter Norvig (2010). Artificial Intelligence. A Modern Approach. 3rd edition. Prentice Hall.
Gerhard Weiss (Ed.) (2013, 2nd edition): Multi-agent Systems. MIT Press.
Mike Wooldridge (2009, 2nd edition): An Introduction to Multi Agent Systems, John Wiley & Sons Ltd.
Yoav Shoham and Kevin Leyton-Brown (2009): Multi-agent Systems. Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press.
More information at: https://curriculum.maastrichtuniversity.nl/meta/462431/agents-and-multi-agent-systems
