Genetic algorithms as a feasible re-planning mechanism for Beliefs-Desires-Intentions agents

Abstract

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.