So is this something that you can implement now?


On Sun, Dec 8, 2013 at 12:08 PM, Piaget Modeler
<[email protected]> wrote:
>
> The first step is carving up the world so that you can talk about it easily.  
>  So we need several categories.
> In the Premise language, we could specify them as follows:
>
> let percept
>   :id
>   :name
> end
>
> let concept
>   :id
>   :name
> end
>
> let action
>   :id
>   :name
> end
>
> let solution
>   :id
>   :before { }
>   :steps  { }
>   :after  { }
> end
>
> let prediction
>   :id
>   :before { }
>   :after  { }
> end
>
> let episode
>   :id
>   :before { }
>   :during { }
>   :after  { }
> end
>
>
> In PAM P2 it's actually more complicated than this but the idea is that you 
> are working at the level
> of solutions most of the time, rather than at the level of actions. Actions 
> are primitive.  If actions are
> encountered they are matched to solutions which contain them, or combined to 
> form new solutions.
> Similarly for percepts (external elements) or concepts (internally 
> synthesized elements).  Percepts
> and concepts are matched to predictions and solutions.
>
> Predictions and solutions are practically the same thing.  The antecedent 
> (:before slot) of a prediction
> is equivalent to both the antecedent and steps slots (:before and :steps) of 
> a solution.
>
> Jim Bromer:  "So how could an AGI program determine that the action produced 
> a kind of reaction
> (that can be used as an intrinsic goal)?"
>
> The answer, is through episode analysis (or episode mining).
>
> So in PAM P2 when an action is taken by the Executor component, all 
> subsequently activated percepts
> and concepts form episodes.  Episodes are the basis of solutions and 
> predictions. Episodes can be
> nested and sequenced. So you capture episodes at multiple levels and then 
> study them for deriving
> predictions, solutions, etc.
>
> Very simple.  This is one approach. Doubtless there are many others.
>
> ~PM


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