Ιntelligent Agents and Multiagent Systems

Learning Outcomes

Upon successful completion of this course, students should be able to

Know principles, paradigmatic architectures and methods for developing single agent and multi agent systems, have a critical and informed view of strengths and limitations regarding agents and multi agent systems, towards designing and delivering such systems.

Specifically, students know and acquire the abilities to develop

• Architectures of single and multi-agent systems
• Methods for agents coordination, collaboration and competition in specific settings and paradigmatic environments and problems
• Agents’ communication methods and protocols

Via the critical view of agents technology and experience in developing such systems.

Course Contents

• Agents: Principles, architectures and application examples
• Deliberation vs Reaction: Architectures
• Mental attitudes, states and their representation
• Multi-agent Systems: Interactions and dependencies
• Multiagent organizations and communication
• Cooperation and collaboration
• Agents communication
• The JASON framework and Agent Speak language

Recommended Readings

• Michael Wooldridge, Introduction to MultiAgent Systems, 2008.
• Yoav Shoham, Kevin Leyton-Brown Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press, 2009.
• Gerhard Weiss, Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press, 2000.
• John Miller Scott Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity), Princeton University Press, 2007.
• David Easley, Jon Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press 2010.
• JASON, https://github.com/jason-lang/jason