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TIMING ANALYSIS OF PREDICATE-LOGIC RULE-BASED SYSTEMS As rule-based expert systems become widely adopted in new application domains such as real-time systems, ensuring that they meet stringent timing constraints in these safety-critical and time-critical environments emerges as a challenging problem. As described in detail in chapter 10, in these systems, a change in the environment may trigger a number of rule firings to compute an appropriate response. If the computation takes too long, the expert system may not have sufficient time to respond to the ongoing changes in the environment, making the result of the computation useless or even harmful to the. | Real-Time Systems Scheduling Analysis and Verification. Albert M. K. Cheng Copyright 2002 John Wiley Sons Inc. ISBN 0-471-18406-3 CHAPTER 11 TIMING ANALYSIS OF PREDICATE-LOGIC RULE-BASED SYSTEMS As rule-based expert systems become widely adopted in new application domains such as real-time systems ensuring that they meet stringent timing constraints in these safety-critical and time-critical environments emerges as a challenging problem. As described in detail in chapter 10 in these systems a change in the environment may trigger a number of rule firings to compute an appropriate response. If the computation takes too long the expert system may not have sufficient time to respond to the ongoing changes in the environment making the result of the computation useless or even harmful to the system being monitored or controlled. To evaluate and control the performance of a real-time expert system it is necessary to relate the quality of a response computed by the expert system to the time available to compute it. Even in a case where response time is not a major concern or a deadline is not imposed the predictability is still a desired quality which may improve the resource utilization or the user productivity. For example if the programmer has a tool to measure an upper bound on the maximal program response time he she will not have to guess whether the program runs into an infinite loop or the program just takes a long time to complete execution thus avoiding unnecessary waiting for the program to complete execution or undesirable interrupting of program execution. This is particularly true for production systems whose rule firing patterns depend on initial working memory contents. Unfortunately rule-based expert systems are computationally expensive and slow. Moreover they are considered less predictable and analyzable because of their context-sensitive control flow and possible nondeterminism. To remedy this problem two solutions are proposed in the literature. The