Without a title - Forgetting in a single-agent scenario

Forgetting in a single-agent scenario

In the scenario of single-agent learning we propose adding KI to a learning algorithm in order to forget some useless rules that have been acquired before. This might seem contradictory as it was said that KI joined the knowledge of several agents into one single theory, and here we are talking about a single agent. Nevertheless, one can take advantage of the architecture and algorithm of KI and apply it to an existing learning algorithm. We illustrate this by the following figure :

Fig. 3 - Use of KI to build a new single-agent learning algorithm.

This can be seen as a single-agent learning algorithm because we give it a set of examples and it produces a theory induced by this set. Inside of it, it is hidden another learning algorithm (which for this discussion is irrelevant) put together with the methodology of KI. This methodology provides a good way of dealing with the problem of forgetting. In this case, KI is used as a technique of pruning rules. This technique is different from others (for example [Cestnik et al., 1987]) as it prunes complete rules instead of parts of rules. For more details regarding the implementation of this strategy into a classical learning algorithm like ID3 see [Torgo,1991b].

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