As speech and natural language processing technology advance, it now reaches a stage where the dialogue control or initiative can be studied to realise usable and friendly human computer interface programs such as computer dialogue systems. One of the major problems concerning dialogue initiative is who should take the dialogue initiative when. This thesis tackles this dialogue initiative problem using the following approaches: 1. Human dialogue data is examined for their local dialogue structures; 2. A dialogue manager is proposed and implemented, which handles variations of human dialogue data concerning the dialogue initiative, and experimental results are obtained by having the implemented dialogue managers working with a parser and a generator exchange natural language messages with each other; and 3. A mathematical model is constructed and used to analyse who should take the dialogue initiative when. The first study shows that human dialogue data varies concerning the number of utterance units in a turn and utterance types independently of the difference of the dialogue initiative. The second study shows that the dialogues in which the dialogue initiative constantly alters (mixed-initiative dialogues) are not always more efficient than those in which the dialogue initiative does not change (non mixed-initiative dialogues). The third study concludes that under the assumption that both speakers solve a problem under similar situations, mixed-initiative dialogues are more efficient than non-mixed-initiative dialogues when initiating utterances can reduce a problem search space more efficiently than responding utterances. The above conclusion can be simplified to the condition that the agent should take the dialogue initiative when s/he can make an effective utterance like in the situations where s/he has more knowledge than the partner with respect to the current goal.
