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The booklet constitutes the completely refereed post-workshop complaints of the 1st Workshop on Bio-Inspired layout of Networks, BIOWIRE 2007, held in Cambridge, united kingdom, in April 2007.
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Additional info for Bio-Inspired Computing and Communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers
Note that we have used the terms of the x xm . form qj j because if the expression were exact, then P [Km ≥ xm ) = gm 4 Logical Dependency of an Agent on Several Others: A First Approach We will now continue exploiting the exact solution provided in (10). In the previous section we have covered the action of some agent i on an agent j, as well as the joint action of agents (i, j) on some third agent l. In this section we would like to consider how a set of agents [a1 , a2 , ... , aα ] and [b1 , b2 , ...
Thus: – As indicated earlier, Ki (t) represents the activation level, amount or concentration level of the agent i. The equations (6) describe the case where any agent i is only activated if Ki (t) ≥ xi ≥ 1. – Through the parameters Λi , the natural replenishment of agent i, for instance via some biochemical reaction, or via inﬁltration from an external medium, is being represented. The parameters λi in turn represent a deletion of agent i. Both Λi and λi are speciﬁc to a single agent and do not represent inter-agent interactions.
Xin with Xij being either Aj or ¬Aj , and they too are disjoint. Clearly we can transform an expression in CNF into DNF and vice-versa using (20). In this section we see how the expression (24) can be used to derive the sate probability for a logical expression in CNF. Let us consider the CNF given in (27) and assume that each literal Aj corresponds to a distinct agent. We will associate an agent AF with the function F with qF = limt→∞ P (KF (t) > 0). 1 that was previously presented. From the above discussion we see that once we have a way of representing the logical expression (19) using a G-network, it is quite direct to obtain the G-network counterpart for an expression in CNF.