Right now I would think that a negative reward would be usable for this aspect. I am using the positive negative reward system right now for motivational/planning aspects for the AGI.
So if sitting at a desk considering a plan of action that might hurt himself or another, the plan would have a negative rating, where another safer plan may have a higher rating.
One possible thing here as well is to have asmall random value added, so that even though a plan has a suboptimal value, it woul dbe possible to take that route instead. (maybe adding in the value of having a new experience here as well)
One important thing we will need here, is an entire KR that will represent all the AGI's past actions, and a way to look back over the actions and compare them to thier expected outcomes, and see why something is different. (Reflection)
IE If the robot proposes to cross the road at a point, sees it as a good plan, and does it, but nearly gets hit by a car, it needs to be able to look back over its actions, and determine that something was missing from his equation, and try to add it back in, or ask a human for assistance, so in the future, he can better handle this activity.
James Ratcliff
On Fri, 09 Jun 2006 19:13:19 -500, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:
>
> What about punishment?
Currently I see it as the programs in control of outputting (and hence
the ones to get reward), losing the control and the chance to get
reinforcement. However experiment or better theory would be needed to
determine whether this is sufficient or negative reward would be
needed.
Will
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