Self-Organizing Agent Systems (SOAS) [UB]

Teaching Points:
Responsible Unit:
Responsible: Maite Lopez-Sanchez, Maria Salamó
Language: English


Autonomic Computing is an initiative started by IBM in 2001. Its ultimate aim is to create self-managing computer systems to overcome their rapidly growing complexity and to enable their further growth. This course approaches this area from the Multi-Agent Systems and Self-Organization point of view:

  • A multi-agent system is one 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.
  • Self-organization is a process in which the internal organization of a system, normally an open system, increases in complexity without being guided or managed by an outside source.

The main objective of this course is to provide an insight of the autonomic capabilities of different multi-agent systems. As a result, students will acquire the capability to discern what applications are suitable for applying open agent-oriented solutions, and how these solutions can adapt to eventual changes automatically.


1. Introduction to Multi-Agent Systems:

  • Social models
  • Cooperative vs competitive agents
  • Contract networks
  • Coalitions
  • Organizations
  • Institutions
  • Application to electronic commerce and negotiation
2. Agent Based Simulation

  • Individual modelling
  • Social analysis
  • Tools & case studies

3. Adaptation & Coordination

  • Coalitions
  • Organizations
  • Autonomic Electronic Institutions
  • Coordination within virtual institutions
  • Multiple Institutions.

4. Adaptive social communities

  • Network communities
  • Survey on Recommender Systems
  • Collaborative Recommender Agents
  • Negotiation in Recommender Agents
  • Conversational Case-Based Reasoning Agents
  • Social Trust for Recommender Agents

5. Physical agents: Autonomous Robots

  • Robot simulators
  • Reactivity
  • Emergence, swarms and social intelligence
  • Behaviour based autonomous robots
  • Robot formations


Simulations and multiagent systems will be implemented in order to explore different application case studies. Most coursework is to be carried out in pairs, although some individual work will also be required.


  • Michael Wooldridge, "An Introduction to Multiagent Systems". John Wiley & Sons 2002. ISBN 0 7149691X.
  • Gerhard Weiss, "Multiagent Systems, A Modern Approach to Distributed Artificial Intelligence", MIT Press, 1999. ISBN 0-262-23203-0

  • Contents of this course are related (but not restricted) to other courses such as: o "E-commerce and agents" by Julian Padget at University of Bath
  • "Multiagent Systems" by Michael Wooldridge at University of Liverpool.
  • "Agents and Multi Agent Systems" by Carles Sierra et al. (IIIA-CSIC)
  • "Biologically-inspired Distributed and Multi-agent Systems" by Radhika Nagpal at Harvard University.
  • "Multiagent Systems" by Javier Vazquez at UPC
  • "Models of Agent Dialogue" by Tim Norman at UPC
  • Additional course material will include somew (but by not means is not restricted to) papers by:
  • Nick Jennings (Southampton Univ)
  • Onn Shehory (IBM)
  • Juan A. Rodriquez-Aguilar (IIIA) , Maite Lopez-Sanchez (UB)
  • Virginia Dignum (Utrecht Univ)
  • Milind Tambe (USC)
  • Barry Smyth (UCD) , Maria Salamó (UB)
  • Gaurav Sukhatme (USC)