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times or more as much. Indonesian planners counted more than Dutch, but the difference was not signi cant (x2 4.71; p , 0.19; df 3). No difference between domains was found (x2 2.85; p , 0.82; df 6). 4.3.2.3.4. Amount of Mistakes. The amount of mistakes indicates that we had to correct the planners if they unjustly thought they were nished; that is, they solved the planning problem (Table 4.13). The kind of categorization (in little, medium, and much) used for counting was also used for mistakes. If they corrected the mistakes themselves, it was not scored. There was an overall tendency of making only a few mistakes, showing no differences between countries (x2 4.95; p , 0.17; df 3) or domains (x2 6.79; p , 0.30; df 6). 4.3.2.3.5. Constraint Relaxation. Although the domains were different, the mathematics behind the problem was the same. The reason we manipulated the planning problem in this way was that we wanted to have information on the problem representation of the planners. We argued earlier that we wanted to nd out whether the domain determines the way planners solve a planning problem. We hypothesized that planners from whatever domain use a general (cognitive) planning strategy. The planning problem was created such that the planner was not able to solve the problem within the constraints. The constraints could be relieved in several ways. Table 4.14 enumerates the constraints mentioned by the planners. It reads as follows. In the staff scheduling problem, for example, the ratio of nurses and doctors could be changed from 3:1 into 2:1 for some days. In the production planning problem the service of one of the machines could be postponed, and in the transportation planning problem the properties of the containers with the products could be changed.

the packet with the smallest timestamp in column ; if the packet being transmitted or just sent out has a start time value of modulo W ., the packet with the smallest time stamp in column , if any, is also moved to the scheduler queue. Each packet is referred to as the first packet in the corresponding column. Based on the above operations, the first packet of each nonempty and eligible column is moved to the scheduler queue, and is prioritized by its finish time. Since each eligible column has at least one packet in the scheduler queue, after the above operations, the remaining packet s. in the same column, if any, will all be moved to the scheduler queue eventually. According to 4.23., V t . may be advanced by more than one in case several columns in the shaper queue are empty. These empty columns fall between the column pointed to by the previous system virtual time and that pointed to by the minimum value of start times among all currently nonempty sessions, which is the current system virtual time based on 4.23.. This can help immediately find the next nonempty and eligible column so that the work-conserving property of the packet scheduler is preserved w6x. Still, only two packets at most need to be transferred to the scheduler queue. Since this mechanism can be used in both ATM and packet switches, we call it the general shaper scheduler. Figure 5.21 illustrates the basic operations of our slotted mechanism when packets enter and leave the scheduler queue. The length of a time slot is regarded as one. From time t to t q 3, there are four arriving HOL packets