AURA solves a problem by drawing conclusions from a given set of facts about the problem. Program does not learn, nor is it self-analytical, but it reaches logical conclusions flawlessly. It used various types of reasoning and, more important, has access to very powerful and sophisticated logical strategies. AURA seldom relies on brute force to find solutions. Instead it
solves almost all problems by using sophisticated techniques to find a contradiction. One generally starts with a set of assumptions and adds a statement that the goal is unreachable. For ex- ample, if the problem is to test a safety system that automatically shuts down a nuclear reactor when instruments indicate a problem, AURA is told that the system will not shut the reactor down under those circumstances. If AURA finds a contradiction between the statement and the system's design assumptions, then this aspect of the reactor's design has been proved satisfactory. This strategy, known as the set of support strategy, lets AURA concentrate on the problem at hand and avoid the many fruitless steps required to explore the entire theory underlying the problem. Almost never does the program proceed by carrying out an exhaustive search.
The chief use for AURA at this time is for electronic circuit design validation, but a number of other uses will arise. For example, there already exist "expert systems" that include a component for reasoning. An expert system is a special-purpose program designed to automate reasoning in a specific area such as medical diagnosis. These expert programs, unlike human experts, do not die. Such systems continue to improve and have an indefinite life span. Moreover, they can be replicated for pennies. A human who can expertly predict where to drill for oil is in great demand. A program that can predict equally well would be invaluable and could be duplicated any number of times.
Will the computer replace the human being? Certainly not. It seems likely that computer programs will reproduce — that is, design more clever computer programs and more efficient, more useful components. Reasoning programs will also analyze their own progress, learn from their attempts to solve a problem, and redirect their attack on a problem. Such programs will assist, rather than replace, humans. Their impact will be felt in design, manufacturing, law, medicine, and other areas. Reasoning assistants will enable human minds to turn to deeper and far more complex ideas. These ideas will be partially formulated and then checked for reasoning flaws by a reasoning program. Many errors will be avoided.
The primary purpose of AURA is to______.
A.function as a safety mechanism in. nuclear reactors
B.detect contradictions and other faults in computer programs
C.develop expert human programs for technical fields
D.check human reasoning for possible errors
第3题
根据《国际载重线公约》的规定,当船舶从内河港口驶出时,________.
A.不允许超载
B.允许超载,但是超载重量应等于从出发港到入海口所需消耗的油水的重量
C.是否允许超载要根据船舶的大小而定
D.以上都不对
第4题
A.操作人员应佩戴防护眼镜
B.操作时应控制冷拉值,不准超载
C.拉直钢筋的两端要有防护措施,防止钢筋拉断或滑离夹具伤人
D.工作中禁止人员站在冷拉机的两端
第6题
通过对钢筋的冷拉,既提高了强度,又节约了材料,下列不属于冷拉机的操作要点的是()。
A.操作时应控制拉值,不准超载
B.运转中不准将手伸人卷筒作清理工作,也不准进行维修
C.工作中禁止人员站在冷拉线的两端
D.用配重控制的设备,工作前要检查配重块与设计要求是否一致
第7题
通过对钢筋的冷拉,既提高了强度,又节约了材料,下列不属于冷拉机的操作要点的是()。
A.操作时应控制拉值,不准超载
B.运转中不准将手伸人卷筒作清理工作,也不准进行维修
C.工作中禁止人员站在冷拉线的两端
D.用配重控制的设备,工作前要检查配重块与设计要求是否一致
第8题
通过对钢筋的冷拉,既提高了强度,又节约了材料,下列不属于冷拉机的操作要点的是()。A.操作时应控制拉值,不准超载B.运转中不准将手伸人卷筒作清理工作,也不准进行维修C.工作中禁止人员站在冷拉线的两端D.用配重控制的设备,工作前要检查配重块与设计要求是否一致
第9题
通过对钢筋的冷拉,既提高了强度,又节约了材料,下列不属于冷拉机的操作要点的是()。
A.操作时应控制拉值,不准超载
B.运转中不准将手伸人卷筒作清理工作,也不准进行维修
C.工作中禁止人员站在冷拉线的两端
D.用配重控制的设备,工作前要检查配重块与设计要求是否一致
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