Aims and learning outcomes

Computer systems are widely recognized to be increasingly distributed and interconnected. This trend naturally leads to the development of systems composed of autonomous entities, called agents, that interact with each other in complex environments. Agent-based systems can be identified in several applications, including electronic commerce, control of industrial processes, ambient intelligence, grid computing, web services, robotics, space systems, and modeling of complex systems. This course aims at presenting general techniques for developing multiagent systems, independently of the applicative domains. In particular, the course will present methods for developing single agents, able to make rational decisions in situations affected by uncertainty, and for developing systems composed of multiple agents, with special emphasis on the interaction between the agents. Moreover, some real-world applications of agent systems will be reviewed. At the end of the course, students will acquire the ability to design and develop distributed systems based on the agent paradigm.

Syllabus

1. Introduction to the concepts of autonomous agent and of multiagent systems.

2. Autonomous agents as rational decision makers: utility function, Markov decision problems, optimal policies.

3. Interaction between agents: some basics and common knowledge.

4. Cooperative interaction between agents: distributed constraint satisfaction problems.

5. Competitive interactions between agents: short introduction to game theory (non-cooperative and cooperative games), negotiations, auctions, voting mechanisms.

6. Real-world applications of agent-based systems.

Prerequisites

Basic programming, algebra, mathematical analysis, probabilities, and mathematical programming.

Further information

For further information about the course:
http://home.deib.polimi.it/amigoni/AutonomousAgentsAndMultiagentSystems.html

The exam is written, with exercises and questions.