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After completing the course, the student
- Knows the main concepts and abstractions that are used in multi-agent systems (e.g., agents, organisations, environment, role, norms, communication, coordination, social commitments, beliefs, desires, intentions)
- Is able to model and analyze interactions in multi-agent systems (e.g., communication, negotiation, interaction protocol)
- Is acquainted with the theoretical aspects and problems of multi-agent systems (autonomous systems, normative systems, compliance with norms)
- Knows basic concepts from decision and game theory (e.g., decision rules, various equilibria, mechanism design, social choice functions, voting mechanisms)
- Is able to work with game theoretic concepts (e.g., determining different equilibria, working with different game settings such as strategic and extensive games, determining winners of various voting mechanism and auctions)
- Recognizes different applications of multi-agent systems (e.g., auctions, electronic institutions, virtual organisations)
- Has insight into the strengths and weaknesses of multi-agent systems (e.g., distributed nature of multiagent systems, situatedness of multi-agent systems, impossibility results from game theory and its relevance for multi-agent systems)
- Recognizes the interdisciplinary nature of multi-agent systems (e.g., the relations between multi-agent systems with social sciences, psychology, and economy)
Assessment
Written exams and assignments.
The tutorial sessions are organized around a student group assignment to design a negotiating agent. The group assignment consists of three written reports and a Java implementation of the negotiation agents.
The individual assignment covers multiagent system issues such as:
- Multi-agent negotiation
- Preference modeling and utility theory
- Communication protocols and coordination in Multi-Agent Systems
- Group decision-making
- Opponent modeling
- Decision-making under uncertainty
- Development of Multi-Agent Systems
Each student is expected to present some papers on one of the abovementioned topics.
To qualify for a repair test, the grade of the original must be at least a 4.
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Multiagent systems are nowadays an important and innovative research area in artificial intelligence and computer science. They are viewed as a computational paradigm to specify, design, and implement software systems for solving complex tasks in terms of interacting computational entities. These computational entities, called agents, are usually assumed to be heterogeneous, autonomous, self-interested, and situated in an environment. They can communicate and coordinate their activities to achieve their objectives.
The environments in which individual agents are situated can be ordinary software environments (e.g., internet), physical environments (e.g., robot), or normative mechanisms (e.g., virtual organization). Multiagent system paradigm can be used to develop open and distributed applications such as multi-robot systems, on-line auctions, virtual organizations, electronic institutions, market places, and virtual games.
Some of multiagent issues are: how agents communicate and interact with each other, how they coordinate their activities, how their activities can be organized, and what are characteristics of multiagent applications.
Course form
Lectures, seminars and lab sessions.
The lectures will cover the following topics:
- Game theory
- Auctions
- Communication
- Social choice
- Mechanism Design
- Normative Multi-Agent Systems
The seminar sessions consists of student presentations and will cover other multi-agent system issues such as:
- Logics for Multi-Agent Systems
- Multi-Agent Organizations and Electronic Institutions
- Normative Multi-Agent Systems
- Argumentation and Dialogues in Multi-Agent Systems
- Multi-Agent Negotiation
- Communication and coordination in Multi-Agent Systems
- Development of Multi-Agent Systems
In the lab sessions the students will develop multi-agent systems on different platforms such as 2APL and Jade.
Literature
We use parts of the following books and some additional papers.
- Yoav Shoham, Kevin Leyton-Brown, "Multiagent Systems Algorithmic, Game-Theoretic, and Logical Foundations", 2009, Cambridge University Press.
- Michael Wooldridge, "An Introduction to Multiagent Systems". Second edition, John Wiley & Sons, ISBN-10:0470519460. Available on the internet.
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