AGENT MEETING SCHEDULER

This dissertation is purposed to record all the data gathered throughout author's
study and research for this project. A deep study of agent algorithm is conducted
based on current available agent meeting scheduler from combination of software
agent and algorithm data structure knowledge. The current problem of typical
meeting scheduler is it is time consuming and inefficient; and also a resource needs
to be allocated to perform the meeting scheduling job. Agent meeting scheduler will
be used to replace this typical meeting scheduler to make it more efficient in term of
deciding meeting time. The study is meant to research and select suitable algorithm
to be implemented in agent meeting scheduler. An agent meeting scheduler
prototype then will be developed to prove that the selected algorithm is working
properly. Qualitative research method is being used to gather necessary data on agent
algorithm and this data will be used to select the suitable algorithm. Through the
research conducted on available algorithm for agent meeting scheduler, genetic
algorithm is selected to be used in this project. The agent meeting scheduler
prototype then will be developed by using PHP language. PHP is selected for its
interactivity and extensibility.