By Richard Benjamins, Christine Pierret-Golbreich (auth.), Nigel Shadbolt, Kieron O'Hara, Guus Schreiber (eds.)
This publication provides the refereed complaints of the ninth eu wisdom Acquisition Workshop, EKAW '96, held in Nottingham, united kingdom, in could 1996.
The 23 revised complete papers incorporated deal with the main suitable theoretical and applicational features of data acquisition with a definite emphasis at the acquisition of information for the modelling or automation of advanced problem-solving behaviour. the quantity is geared up in sections on theoretical and normal concerns, eliciting wisdom from textual or different resources, data-mining, workforce elicitation, and planning.
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Extra info for Advances in Knowledge Acquisition: 9th European Knowledge Acquisition Workshop, EKAW '96 Nottingham, United Kingdom, May 14–17, 1996 Proceedings
We argue that these approaches are restrictive in nature as they only focus on preserving the context rather than ﬁnding a new and better one P. Collet et al. ): EuroGP 2006, LNCS 3905, pp. 36–48, 2006. c Springer-Verlag Berlin Heidelberg 2006 A Less Destructive, Context-Aware Crossover Operator for GP 37 in the child. Brood recombination  has solved this problem to some extent by generating multiple children. Unfortunately, this does not guarantee the use of the selected subtrees in the best possible contexts in the produced children.
A two–dimensional mapping with a strange attractor. Communications of Mathematical Physics 50 (1976) 69–77 9. : Time Series Modelling of Water Resources and Environmental Systems. ie Abstract. Standard GP crossover is widely accepted as being a largely destructive operator, creating many poor oﬀspring in the search for better ones. One of the major reasons for its destructiveness is its disrespect for the context of swapped subtrees in their respective parent trees when creating oﬀspring. At times, this hampers GP’s performance considerably, and results in populations with low average ﬁtness values.
2nd edn. Springer (1997) 2. : Complexity–based induction systems: comparisons and convergence theorems. IEEE Trans. on Information Theory IT–24 (1978) 422–432 3. : Progress in incremental machine learning. C. (2002) 4. : A formal theory of inductive inference. Information and Control 7 (1964) 1–22, 224–254 5. : Genetic Programming: on the programming of computers by means of natural selection. MIT Press, Cambridge, Massachusetts (1992) 6. : A representation for the adaptive generation of simple sequential programs.