jmpj0611

Granting AI user-input priority over internal chains of thought.

We expect the AI Mind to activate incoming concepts mentioned during user input, so that the AI can talk to us about things we mention. Recently, however, the SpreadAct() module has been putting quasi-neural activation only on concepts thought about internally but not mentioned during user input. We need a way to let user-input override any activation being imposed by the SpreadAct() module for internal chains of thought, so that external input takes precedence. One method might be to use the quiet variable and set it to "false" not only during user input but also until the end of the first AI output made in response to user input. In that way, any concept mentioned by the user could briefly hold a high activation-level not superseded by the machinations of the SpreadAct() module for spreading activation. We implement the algorithm, and the AI then responds properly to user input. We solve some other problems, such as KbRetro() interfering with the conceptual engrams of an inference, and negation not being stored properly for negated ideas.