Abstract: A search agent training system includes a trainer device. The trainer device includes a trainer network simulation of variable size, which further includes at least one selectable action, at least one selectable node, and a trainer knowledge base, which further includes at least one selectable action outcome probability value. The trainer knowledge base is populated by a quantification system. The trainer device receives an incoming action message from a search agent device including a selected action and a selected node. Next, based upon: a resulting action outcome probability value, the selected action, and the selected node, a resulting observation and a resulting reward is sent to the search agent device. The trainer device blocks node count report messages to the search agent device from the trainer device.

Abstract: A search agent training system includes a trainer device. The trainer device includes a trainer network simulation of variable size, which further includes at least one selectable action, at least one selectable node, and a trainer knowledge base, which further includes at least one selectable action outcome probability value. The trainer knowledge base is populated by a quantification system. The trainer device receives an incoming action message from a search agent device including a selected action and a selected node. Next, based upon: a resulting action outcome probability value, the selected action, and the selected node, a resulting observation and a resulting reward is sent to the search agent device. The trainer device blocks node count report messages to the search agent device from the trainer device.