Truth Maintenance Under Uncertainty
نویسنده
چکیده
This paper addresses the problem of resolving errors under uncertainty in a rule-based sys tem. A new approach has been developed that reformulates this problem as a neural-network learning problem. The strength and the fun damental limitations of this approach are ex plored and discussed. The main result is that neural heuristics can be applied to solve some but not all problems in rule-based systems.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1304.2353 شماره
صفحات -
تاریخ انتشار 2011