Knowledge-Based Systems in Artificial Intelligence: 2 Case Studies
Knowledge-Based Systems in Artificial Intelligence: 2 Case Studies
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Bootstrap is a technique which permits the operational state of a system to bring itself into another operational state by means of its own action[1]. It has been claimed in past that the system architecture at the time of bootstrap can be well-configured as delta functions[2--3] as AM[4] has shown us. The use of such heuristics lead to new domain concepts, facts and new judgemental rules. This enforced learning by discovery. However, questions still remain open: how the system is going to know about the time and place for having a bootstrap? Several examples have been worked out where the infra-structure permitting bootstrap is constructed out of a set of ground atomic formulea. It is also enquired what will be the consequence if only a partial set of these atomic formulea are known. Attempts have been made to see whether these atomic formulea increase monotonically in time, and consequently, what will be the nature of default reasoning learned from non-monotonicity. Finally, it is claimed that machine learning of clustured concepts are possible that predict times and places of bootstraps definable under specialized atomic formulea generating the infra-structure.