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where is a multiplying factor and round returns the closest integer The ALCs in the cloned set, W, are mutated with a mutation rate that is inversely proportional to the calculated a nity, ie a higher a nity implies a lower rate of mutation The mutated clones in W are added to a set of mutated clones, W The a nity between the mutated clones in W and the selected training pattern, zp , is calculated The ALC with the highest calculated a nity in W , x, replaces the ALC at position, p, in set M, if the a nity of x is higher than the a nity of the ALC in set M Randomly generated ALCs replace nl of the lowest a nity ALCs in R The learning process repeats, until the maximum number of generations, tmax , has been reached A modi ed version of CLONALG has been applied to multi-modal function optimization [190]

.

(d) = 3 /4

The Message Server by itself cannot send or receive any messages, as it does not contain the message-type-speci c knowledge required. Instead,

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In some cases the problem that needs to be optimized consists of self patterns that changes through time To address these types of problems, the dynamic clonal selection algorithm (DCS) was introduced by Kim and Bentley [461] The dynamic clonal selection algorithm is based on the AIS proposed by Hofmeyr [372] The basic concept is to have three di erent populations of ALCs, categorized into immature, mature and memory ALC populations Kim and Bentley [461] explored the e ect of three parameters on the adaptability of the model to changing self These parameters were the tolerization period, the activation threshold and the life span The tolerization period is a threshold on the number of generations during which ALCs can become self-tolerant The activation threshold is used as a measure to determine if a mature ALC met the minimum number of antigen matches to be able to become a memory ALC The life span parameter indicates the maximum number of generations that a mature ALC is allowed to be in the system If the mature ALC s life span meets the pre-determined life span parameter value, the mature ALC is deleted from the system The experimental results with di erent parameter settings indicated that an increase in the life span with a decrease in the activation threshold resulted in the model to have an increase in detecting true nonself patterns An increase in the tolerization period resulted in less self patterns being detected falsely than non-self patterns, but only if the self patterns were stable With a changing self the increase in tolerization period had no remarkable in uence in the false detection of self patterns as non-self patterns Although the DCS could incrementally learn the structure of self and non-self patterns, it lacked the ability to learn any changes in unseen self patterns The memory ALCs in the DCS algorithm had in nite lifespan This feature was omitted in the extended DCS by removing memory ALCs that were not self-tolerant to newly introduced self patterns [460] A further extension to the DCS was done by introducing hyper-mutation on the deleted memory ALCs [459] The deleted memory ALCs were mutated to seed the immature detector population, ie deleted memory ALCs form part of a gene library Since these deleted memory ALCs contain information (which was responsible for giving them memory status), applying mutation on these ALCs will retain and ne tune the system, ie reinforcing the algorithm with previously trained ALCs.

Fig 22 Ellipse forms are depicted for phase differences x ) D of 0 (a), /4 (b), /2 (c) and 3 /4 (d), with ( y the orthogonal amplitudes, E x0 , E y 0 , equal to each other For D 0, linear polarization ensues; for D /2, with equal component amplitudes, circular polarization results The sense of description of the ellipse gures depends on the sign of the phase difference (see the text)

Knight and Timmis [468] proposed a novel clonal selection inspired model that consists of multi-layers to address some of the shortfalls of the AINE model as discussed in Section 194 The de ned layers interact to adapt and learn the structure of the presented antigen patterns The model follows the framework for an AIS as presented in [182] The basic requirements in [182] for an AIS are the representation of the components (like B-Cells), the evaluation of interactions between these components or their environment (a nity) and adaptability of the model in a dynamic environment

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the Message Server uses MTMs that encapsulate the message-type-speci c knowledge MTMs have been created by Symbian and by phone manufacturers for a range of message types, including: email (IMAP, SMTP and POP3) fax SMS BIO messages (smart messages used for con guration and other purposes) infrared and Bluetooth OBEX messages MMS Over time, it has proved straightforward to add new MTMs for new message types the architecture has proved its worth The MTMs are responsible for creating and sending messages, for receiving messages and for some aspects of displaying messages Actually, some types of messages are received by means of watchers (SMS is one of these message types), but the general picture holds true.

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