The BDI agent architecture includes a plan library containing
pre-defined plans. The plan library is included in the agent architecture to reduce the need for expensive means-end reasoning, however can hinder the agent’s effectiveness when operating in a changing environment. Existing research on integrating different planning methods into the BDI agent to overcome this limitation include HTNs, state-space planning and Graphplan. Genetic Algorithms (GAs) have not yet been used for this purpose.
This dissertation investigates the feasibility of using GAs as a plan
modification mechanism for BDI agents. It covers the design of a plan
structure that can be encoded into a binary string, which can be operated on by the genetic operators. The effectiveness of the agent in a changing environment is compared to an agent without the GA plan modification mechanism.
The dissertation shows that GAs are a feasible plan modification mechanism for BDI agents. / Information Science
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:uir.unisa.ac.za:10500/19147 |
| Date | 05 1900 |
| Creators | Shaw, G. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | 1 online resource (159 leaves) |
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