Multi-Agent Systems


  1. To introduce the student to the concept of an agent and  multi-agent systems, and the main applications for which they are appropriate;
  2. To introduce the main issues surrounding the design of intelligent agents;
  3. To introduce the main issues surrounding the design of a multi-agent society.
  4. To introduce a contemporary platform for implementing agents and multi-agent systems.


1       Introduction (1 week)

  • what is an agent?:  agents and objects; agents and expert systems; agents and distributed systems; typical application areas for agent systems.

2    Intelligent Agents (3 weeks)

  • the design of intelligent agents – reasoning agents (eg AgentO), agents as reactive systems (eg subsumption architecture); hybrid agents (eg PRS); layered agents (eg Interrap)
  •  a contemporary (Java-based) framework for programming agents (eg the Jack language, the JAM! system).

3   Multi-Agent Systems (5 weeks)

  • Classifying multi-agent interactions – cooperative versus non-cooperative; zero-sum and other interactions; what is cooperation? how cooperation occurs – the Prisoner’s dilema and Axelrod's experiments; (1 week)
  • Interactions between self-interested agents:  auctions & voting systems:  negotiation; (2 weeks)
  • Interactions between benevolent agents:  cooperative distributed problem solving (CDPS), partial global planning; coherence and coordination; (1 week)
  • Interaction languages and protocols:  speech acts, KQML/KIF, the FIPA framework. (1 week)

 4      Advanced topics (2 weeks):

  • One issue selected from the contemporary research literature, perhaps by guest lecturer.

Recommended Texts

No specific text

Learning Outcomes

  1. Understand the notion of an agent, how agents are distinct from other software paradigms (eg objects) and understand the characteristics of applications that lend themselves to an agent-oriented solution;
  2. Understand the key issues associated with constructing agents capable of intelligent autonomous action, and the main approaches taken to developing such agents;
  3. Understand the key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems
  4. Understand the main application areas of agent-based solutions, and be able to develop a meaningful agent-based system using a contemporary agent development platform.

Learning Strategy

Formal lectures:

Students will be expected to attend three hours of formal lectures in a typical week.

Private study:

In a typical week, students will be expected to devote a further seven hours of unsupervised time to private study. The time allowed for private study each week will typically include three hours of time for reflection and consideration of lecture material, and four hours of background reading.