Degree: Master of Science in Engineering
Department: Engineering / Multi-Agent Systems are becoming a popular paradigm for many engineering applications. However, there is still much research to be performed in this fast growing field. In this thesis, the effect of learning in multi-agent systems on communication and
collaboration between agents is investigated. This research focuses on agents learning local cooperative behaviour from a centralised agent, as well as using learning to reduce the amount of communication between agents that use negotiation to achieve their goals.
A simple test problem is formulated in MATLAB. The effect of learning is clearly seen to reduce the amount of communication between agents by up to 50%, while still
maintaining cooperative behaviour. The agents are also demonstrated to learn to a large degree cooperative local behaviour from a central system.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/351 |
Date | 24 April 2006 |
Creators | Van Aardt, Bradley Justin |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | 433057 bytes, application/pdf, application/pdf |
Page generated in 0.0019 seconds