By D. Paul Benjamin (auth.), Pavel B. Brazdil, Kurt Konolige (eds.)
This ebook features a choice of papers awarded on the foreign Workshop laptop studying, Meta-Reasoning and Logics held in inn de Mar in Sesimbra, Portugal, 15-17 February 1988. the entire papers have been edited afterwards. The Workshop encompassed numerous fields of man-made Intelligence: desktop studying, trust Revision, Meta-Reasoning and Logics. the target of this Workshop used to be not just to deal with the typical concerns in those parts, but in addition to check tips on how to intricate cognitive architectures for platforms able to studying from adventure, revising their ideals and reasoning approximately what they understand. Acknowledgements The enhancing of this ebook has been supported via COST-13 venture computer studying and information Acquisition funded by means of the fee o/the ecu groups which has lined a considerable a part of the prices. different sponsors who've supported this paintings have been Junta Nacional de lnvestiga~ao Cientlfica (JNICT), lnstituto Nacional de lnvestiga~ao Cientlfica (INIC), Funda~ao Calouste Gulbenkian. I desire to show my gratitude to some of these associations. ultimately my exact because of Paula Pereira and AnaN ogueira for his or her assist in getting ready this quantity. This paintings integrated retyping the entire texts and getting ready the camera-ready replica. creation 1 1. Meta-Reasoning and laptop studying the 1st bankruptcy is worried with the position meta-reasoning performs in clever platforms able to studying. As we will be able to see from the papers that seem during this bankruptcy, there are essentially assorted faculties of thought.
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Additional info for Machine Learning, Meta-Reasoning and Logics
In cases where little or no structuring information is available for the version space for a given node, the connectionist approach can help to induce additional structure and generate new terms to simplify the overall concept description. From the point of view of the connectionist enterprise, the knowledge-based derivation of the tree-structured bias provides an ideal way to integrate prior knowledge into a connectionist learning system, since it strongly restricts the typically enormous weight spaces that would otherwise be searched.
The natural process for identifying the correct rule is simply to identify the correct rule for each subtree in a bottomup fashion, by generating experiments that vary the features in the subtree, keeping other features constant. Since, by construction, internal modes of the tree are not easily observable, the induction process is far trivial. Warmuth (personal communication) has shown that a general solution to this problem using random sampling is intractable if one-way functions exist. , experiments) is unknown.
This section concludes with a brief discussion on the use of nonmonotonic reasoning to handle noise in the domain or observations that are inconsistent with the original bias. e. the candidate concept descriptions. Effectively, each C. will resolve against an instance that contradicts it, with the J help of the articulation theory ThQ' Thus as more instances are observed, the DDA will shrink, retaining only those concept descriptions that are consistent with all the instances. 5 shows the resolution process for the simple case of the version space for a single unary predicate, with one negative instance and one positive instance.
Machine Learning, Meta-Reasoning and Logics by D. Paul Benjamin (auth.), Pavel B. Brazdil, Kurt Konolige (eds.)