Reliability assessments of AI programs must consider not only possible program bugs which. remain in the program due to insufficient testing and debugging, but also faults due to intrinsic characteristics of AI programs that cannot be removed even after the program is fully debugged. This paper develops an analytical tool for assessing the reliability of AI programs. Possible intrinsic faults of AI programs are identified, and modifications to existing software reliability models for conventional programs are suggested. An example illustrating the effect of intrinsic faults of AI heuristics on the program reliability in a real-time situation is given. It is shown that under certain conditions the cost-based A* planning algorithm is less reliable than the node-based A* planning algorithm.
['Farokh B. Bastani', 'Ing-Ray Chen']
ASSESSMENT OF THE RELIABILITY OF AI PROGRAMS