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Multiagent Systems - Overview

Lecturers: Prof. Dr. Bernhard Nebel and Prof. Dr. Felix Lindner (Juniorprof.)

Exercises: Dr. Thorsten Engesser

Time and Location

Lecture: Monday 10:15-11:45 and Thursday 14:15-15:00
Exercises: Thursday 15:15-16:00
Location: Building 51, SR 03-026

Exam

The written exam will take place on august the 22th in room 101-00-026 (i.e. building 101, lecture hall 26). The exam starts at 10:15 a.m. lasting 90 minutes.

The exam review will take place on october the 25th, 14:00 in building 052, room 00-043.

Language

The lecture will be given in English.

Description

Multi-agent systems have emerged as one of the most important areas of research and development in information technology. A multi-agent system is composed of multiple interacting software components known as agents, which are typically capable of cooperating to solve problems that are beyond the abilities of any individual member. Multi-agent systems are important primarily because they have been found to have very wide applicability. The difference between agents and objects from OOP could be stated as: "Objects do it for free, but agents do it for money”. This course will address theoretical and practical aspects of multiagent systems. The rationale behind modeling problems in terms of agents in computer science and robotics will be explained. We will see how this approach is different from and relates to other programming paradigms, and which types problems can be solved using agent architectures.

Topics

Topics of this course are:
  • Agent architectures
  • Agent planning
  • Methods of communication
  • Game Theory
  • Common sensing and world modeling
  • Distributed decision making
  • Cooperation and coordination

Prerequisites

The course has a strong focus on practical solutions to multi-agent systems. Therefore, programming skills in Python are mandatory. Furthermore, knowledge of concepts from the lecture Foundations of Artificial Intelligence (Grundlagen der Künstlichen Intelligenz), such as search methods, and probabilistic methods, is useful.

Literature

  • [Wooldridge 2009] An Introduction to MultiAgent Systems - Second Edition.
  • [Russell & Norvig 2003] Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, second edition, Prentice Hall, 2003.
  • [Jeffrey Rosenschein & Gilad Zlotkin 1998] Rules of encounter: designing conversations for automated negotiation among computers, MIT Press
  • [Yoav Shoham & Kevin Layton-Brown 2009] Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press