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＜E-Book＞
Analogical and Inductive Inference : International Workshop AII '92, Dagstuhl Castle, Germany, October 5-9, 1992. Proceedings / edited by Klaus P. Jantke
(Lecture Notes in Artificial Intelligence. ISSN:29459141 ; 642)

Edition	1st ed. 1992.
Publisher	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Year	1992
Language	English
Size	X, 326 p : online resource
Authors	Jantke, Klaus P editor SpringerLink (Online service)
Subjects	LCSH:Artificial intelligence LCSH:Software engineering LCSH:Computer programming FREE:Artificial Intelligence FREE:Software Engineering FREE:Programming Techniques
Notes	Representing the spatial/kinematic domain and lattice computers -- A solution of the credit assignment problem in the case of learning rectangles -- Learning decision strategies with genetic algorithms -- Background knowledge and declarative bias in inductive concept learning -- Too much information can be too much for learning efficiently -- Some experiments with a learning procedure -- Unions of identifiable classes of total recursive functions -- Learning from multiple sources of inaccurate data -- Strong separation of learning classes -- Desiderata for generalization-to-N algorithms -- The power of probabilism in Popperian FINite learning -- An analysis of various forms of ‘jumping to conclusions’ -- An inductive inference approach to classification -- Asking questions versus verifiability -- Predictive analogy and cognition -- Learning a class of regular expressions via restricted subset queries -- A unifying approach to monotonic language learning on informant -- Characterization of finite identification -- A model of the ‘redescription’ process in the context of geometric proportional analogy problems -- Inductive strengthening: The effects of a simple heuristic for restricting hypothesis space search -- On identifying DNA splicing systems from examples This volume contains the text of the five invited papers and 16 selected contributions presented at the third International Workshop on Analogical and Inductive Inference, AII `92, held in Dagstuhl Castle, Germany, October 5-9, 1992. Like the two previous events, AII '92 was intended to bring together representatives from several research communities, in particular, from theoretical computer science, artificial intelligence, and from cognitive sciences. The papers contained in this volume constitute a state-of-the-art report on formal approaches to algorithmic learning, particularly emphasizing aspects of analogical reasoning and inductive inference. Both these areas are currently attracting strong interest: analogical reasoning plays a crucial role in the booming field of case-based reasoning, and, in the fieldof inductive logic programming, there have recently been developed a number of new techniques for inductive inference HTTP:URL=https://doi.org/10.1007/3-540-56004-1

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