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Indirect CRLs are another alternative for improving the distribution of CRLs. As the name implies, an indirect CRL is provided to the relying party by a third party that did not necessarily issue the certificate. In this way, CRLs that otherwise would be supplied by numerous CAs (or other revoking authorities) can be consolidated into a single CRL for distribution. For example, suppose that a private PKI is served by multiple CAs. By using indirect CRLs, the PKI can receive one CRL issued by one CA (or other trusted third party) on behalf of the other CAs. Two CRL extensions enable the use of indirect CRLs. To indicate that a CRL contains revocation information from multiple CAs, the Indirect CRL attribute is set to True. It s also important to provide the relying party with additional information concerning revocation of each entry. A CRL entry for each certificate is used to identify its CA. If there is no CRL entry, the certificate is assumed to have been issued by the CA listed on the first line of the CRL.

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In a normal control algorithm the robot observes the environmental conditions using sensors These values are compared to a set of desired values that have been xed by the programmer Depending on the deviations of the sensory values from the desired ones, the algorithm will determine a course of action that is translated into a set of commands to actuators (eg, motors) that manipulate the robot and/or environment (see Fig 161) The above would result in an environmental change, which then affects the sensory inputs The algorithm continues in a loop, responding to changes due to the actuators of the robot and/or external environmental factors The outcome is that the robot will get progressively closer to the desired state.

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How quickly and how ef ciently the robot reaches the desired state, and how quickly it responds to a disturbance in the conditions depends on the control algorithms used The eld of control is a specialized and exciting eld of study and can be very mathematical The methods for determining the parameters of the algorithm are the subject of a well-established discipline in engineering that uses complex mathematics and calculus to optimize these parameters The analysis to determine the parameters usually takes into account a certain range of environmental criteria but this range is often xed and limited If, instead of xing the parameters forever, the robot is given another feedback loop mechanism that serves to automatically modify the parameters in memory (and keep the parameters that work best), the robot would be able to adapt to a wider range of changing environmental situations The diagram in Fig 16.

2 shows the modi ed adaptive feedback loop Inputs from the decoded sensory data are stored in memory along with the actions that the robot took in response to those inputs The memory is then consulted whenever the robot is to take.

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At times, a CA needs to limit the use of a certificate temporarily but does not require that it be revoked. For example, a corporate end user may be going on vacation. In such cases, the certificate can be suspended, disabling the use of PKI-enabled applications that should not be accessed in the employee s absence. When the employee returns, the CA removes the suspension. This approach saves the CA time by not requiring it to revoke and then reissue the certificate. To suspend a certificate, the CA uses the value Certificate Hold in the Reason Code extension of the CRL.

The program for the PICBASIC Pro compiler is as follows:

Decoded Actuation sensory data Comparison Sensory Variable parameters commands logic deviations adaptive algorithm Desired sensory data

Like end users, CAs themselves are identified by certificates. Just as end user certificates may require revocation, so do CA certificates. An authority revocation list (ARL) provides a means of disseminating this revocation information for CAs. ARLs are distinguished from CRLs via the Issuing Distribution Point field within the revocation list.

action to determine if a favorable or detrimental actuation was experienced in the past, and thus modify the parameters and logic of the algorithm if needed A programmer can also affect the robot s behavior by lling the memory with appropriate data, effectively teaching the robot certain responses and behaviors An example of this was given in Chap 15 where a map was provided to enable the robot to plan an optimal path through the of ce Let us consider how adaptive behavior algorithms can be applied to two algorithms we have encountered in previous chapters 1611 ADAPTIVE WALL-FOLLOWING In Chap 8 a contour-following algorithm used a ranging sensor to determine how far the robot was from the wall The robot turned toward the wall when it got too far from it and away from the wall when it became too close.