Using the bottom clause and mode declarations in FOL theory revision from examples

Theory revision systems are designed to improve the accuracy of an initial theory, producing more accurate and comprehensible theories than purely inductive methods. Such systems search for points where examples are misclassified and modify them using revision operators. This includes trying to add antecedents to clauses usually following a top-down approach, considering all the literals of the knowledge base. Such an approach leads to a huge search space which dominates the cost of the revision process. ILP Mode Directed Inverse Entailment systems restrict the search for antecedents to the literals of the bottom clause. In this work the bottom clause and mode declarations are introduced in a first-order logic theory revision system aiming to improve the efficiency of the antecedent addition operation and, consequently, also of the whole revision process. Experimental results compared to revision system FORTE show that the revision process is on average 55 times faster, generating more comprehensible theories and still not significantly decreasing the accuracies obtained by the original revision process. Moreover, the results show that when the initial theory is approximately correct, it is more efficient to revise it than learn from scratch, obtaining significantly better accuracies. They also show that using the proposed theory revision system to induce theories from scratch is faster and generates more compact theories than when the theory is induced using a traditional ILP system, obtaining competitive accuracies. This is an extended and revised version of the ILP 2008 paper (Duboc et al. 2008).     

Some methodological deficiencies in studies on traffic accident predictors

The paper discusses some methodological problems in (psychological) research on traffic accident predictors and reviews a convenience sample of the literature. Three methodological aspects are identified as being important: reliability of accident predictors, time period for accidents used as dependent variable, and culpability for accidents. Papers are scrutinized and most are found to be wanting in these aspects. Traffic researchers do not adhere to, or hardly even discuss, these basic methodological problems. It is concluded that the current research into (psychological) accident predictors is fraught with methodological deficiencies. Why most studies seem to be deficient in these aspects is not clear, as several researchers have pointed out these problems.