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Table 1 Illustrative Empirical Discoveries Made Within Evolutionary Psychology
"... In PAGE 2: ... These include universal sex differences in long-term mate preferences (Buss, 1989b; Kenrick amp; Keefe, 1992), short-term sexual strategies (Greiling amp; Buss, 2000), the reasons women engage in extrapair copulations (Gangestad amp; Cousins, in press), stepparenting as the most important risk factor for preschool child abuse (Daly amp; Wilson, 1988), cheater- detection procedures in social exchange (Cosmides amp; Tooby, 1992), the specificity of social betrayal depending on relationship context (Shackelford amp; Buss, 1996), why men and women have trouble being just friends (Bleske amp; Buss, 2000), waist-to-hip ratio as a universal standard of attractiveness (Singh, 1993), the importance of symmetry in human mating (Gangestad amp; Thorn- hill, 1997), the centrality of genetic relatedness to the performance of life-or-death acts of altruism (Burnstein et al., 1994), the im- portance of mate-value discrepancies in predicting dramatic acts of mate guarding (Buss amp; Shackelford, 1997), and many others (see Table1 ). By any reasonable standard, evolutionary psychology has discovered an impressive array of empirically documented phe- nomena that were not discovered by prior mainstream nonevolu- tionary psychologists.... ..."
Table 2. Different computational logic issues in inductive logic programming.
"... In PAGE 6: ...1 An analysis The 31% of computational logic oriented work in inductive logic programming can be further classified according to the topic addressed. The most important results are shown in Table2 . The table clearly shows that the main issues are program synthesis and rules and frameworks for inductive inference.... ..."
Table 3 Empirical Phenomena Associated With Analogical Inference and Schema Induction
"... In PAGE 23: ... Simulations of Human Relational Inference and Generalization We will now illustrate LISA apos;s ability to simulate a range of empirical phenomena concerning human relational inference and generalization. Table3 provides a summary of 15 phenomena that we take to be sufficiently well-established that any proposed theory will be required to account for them. We divide the phenomena into those related to the generation of specific inferences about a target, those related to the induction of more abstract relational schemas, and those that involve interactions between schemas and inference.... ..."
Table 9: Induction variables
"... In PAGE 23: ...Table 9: Induction variables Table9 displays the variables which have been analysed during the inductive analysis. (Nu- merical variables are represented by numbers and logical variables are represented by combining similar data into groups, e.... ..."
TABLE 1.2. The inductive and deductive complexity of empirical hypotheses.
Table 4: The 33 wrapper induction tasks used in the empirical evaluation.
"... In PAGE 22: ... These tasks, which were previously used in the literature (Muslea et al., 2003; Muslea, 2002), are brie y described in Table4 . We use 20-fold cross-validation to compare the performance of Naive and Aggressive Co-Testing, Random Sampling, and Query-by-Bagging on the 33 tasks.... ..."
Table 4: The 33 wrapper induction tasks used in the empirical evaluation.
"... In PAGE 22: ... These tasks, which were previously used in the literature (Muslea et al., 2003; Muslea, 2002), are briefly described in Table4 . We use 20-fold cross-validation to compare the performance of Naive and Aggressive Co-Testing, Random Sampling, and Query-by-Bagging on the 33 tasks.... ..."
Table 1: Induction Variables
"... In PAGE 12: ... Also, parts of induced rules rather than whole induced rules may suggest patterns worthy of closer examination. The variables used are summarised in Table1 and the nal induction database with the logical groupings implemented is shown in Table 2 It is important when applying techniques such as rule induction to plan in advance which data needs to be collected. Traditional statistical approaches demand values for dependent and independent variables, but these alone are frequently inadequate for the successful application of classi cation approaches.... ..."
Table 1: Comparison of techniques for the induction of recursive logic programs
1999
"... In PAGE 11: ...iques are overviewed in Section 3.3. Finally, in Section 3.4, we point out cross-fertilisation opportunities and identify directions for future work. The comparison chart ( Table1 ) at the end of this section will be helpful towards this aim, and it may be a good idea for the reader to briefly study it right now. Techniques that are somehow related to some others, or representative thereof, and techniques that are somehow more sophisticated and powerful (in an absolute, application-independent sense) than others will obviously get more coverage here than those that are completely different from all others, or that feature highly specialised (sub-)machinery that is impossible to explain in the allotted space, or whose power is quite limited.... In PAGE 28: ...3.4 Summary We now summarise our overview by means of a chart (see Table1 ). The top five lines name classification criteria, whereas the bottom sixteen lines name actual comparison criteria and features, so that the techniques may be meas- ured up to each other.... In PAGE 35: ... The two approaches can thus be considered complementary, rather than rivals, and the ultimate decision of which one to use should lie with the specifier, not with the research community. So then, what is our statement on the future of the inductive synthesis of recursive programs applied towards pro- gramming assistance? We believe such techniques can be (made) viable, provided more research is done on over- coming the obstacles listed above, provided more realistic programming scenarios are aimed at, and provided the future work directions and cross-fertilisation opportunities of Table1 are pursued. We believe that some categories of programmers would use such techniques, provided it improves their productivity or increases the class of pro- grams they can write by themselves.... ..."
Cited by 25
TABLE 4. Inductive inference SAT problems: 32-variable hidden logic
1998
Cited by 13
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