Concept of Knowledge Plane

 

      Knowledge Distance:

 

            Defined as the distance in knowledge measured in terms of the

            the self-model and the alien-model of the set of all other chronobots taking part

            in the process of negotiation                    

 

            Can be formulated also in terms of the Exchange rate between the agents, where

            Exchange rate is more formally defined as:

            

      Exchange (agent x, agent y) = e  ( 1  /  ∑ Cji * d  ( xji ,  yji ) ) 

 

        where

   

        The summation is over all the terms Cji * d(xji, yji) and

        Cji is a scaling constant

 

 

 

Knowledge Plane:   

 

 

      We describe the Knowledge Plane function Φ in terms of k,

 

      the knowledge distance between the negotiating entities. When the

 

      max of the knowledge distance among all participating chronobots

 

      exceeds threshold t, the knowledge plane function is responsible for

 

      transferring to the higher plane of knowledge

 

Example:

Let us assume that there are two chronobot agents A1 and A2 in the system.

The self-model of A1 includes the current set of values for the various criteria and the weights that A1 assigns for each of those criteria. Similarly the self-model of A2 includes the current set of values for the various criteria and the weights that A2 assigns for each of those criteria.

Let chronobot A2 initiate the bid. The alien-model of A1 includes the current set of values that it assigns to the multitude of criteria specified by A2. Now in order to concretely specify the knowledge distance between A1 and A2 we assume that C1 d1 (x1, y1) = 0. This means that A1 and A2 are in the same knowledge plane and their primary skills match. For instance, if C1 is 10,000 and d1 is between 0 and 1, in this case close to 1.  Then C1 d1 (x1, y1) is close to 100,000 and the exchange rate is close to 1. In this case A1 and A2 are in different Knowledge planes. Henceforth we need to use the Knowledge Plane function, Φ in order to scale the knowledge distance as follows. Since their primary skills do not match, we need to look at the correlation in terms of the programming language skills. Lets assume in this case that C2 d2 (x2, y2) is small. Then we have ensured that A1 and A2 in the same Knowledge Plane and hence A1 can satisfy A2’s bid.