The BDI agent architecture includes a plan library containing pre-de ned
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
e ectiveness when operating in a changing environment. Existing research
on integrating di erent 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
modi cation 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 e ectiveness 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:umkn-dsp01.int.unisa.ac.za:10500/19147 |
Date | 05 1900 |
Creators | Shaw, G. |
Contributors | 1 online resource (159 leaves) |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Dissertation |
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