Multiagent Systems [URV]

Teaching Points:
Responsible Unit: LSI
Language: English


The main objective of this subject is to make an introduction to the basic concepts in the area of intelligent agents and multi-agent systems. A more specific set of objectives is the following:

  • Know how to distinguish between agents and programs that apply Artificial Intelligence techniques.
  • Learn the differences between reactive and deliverative systems, and know when to apply each of them.
  • Understand the basic aspects concerning interface agents and information agents.
  • Discover in which kind of problems it is appropriate to use multi-agent systems.
  • Learn the basic aspects of a standard for agent communication: mult-agent system architecture, communication language, communication protocols.
  • Understand the importance of ontologies in the communication within a multi-agent system.
  • Learn cooperation mechanisms between the components of a multi-agent system.


1. Intelligent agents
  • Agent characteristics
  • Deliberative vs reactive agents
  • Reactive agents
  • Architectures of reactive systems
  • Deliberative agents
  • BDI architecture
  • Types of agents
  • Interface agents
  • Information agents
2. Multi-Agent Systems
  • Advantages of multi-agent systems
  • Communication techniques
  • Blackboard systems
  • Message passing
  • Foundation for Intelligent Physical Agents
  • Architecture of a multi-agent system
  • Agent communication language
  • Communication protocols
  • Ontologies
  • Cooperation among agents
  • Partial global planning
  • Negotiation