We prove that the set of all recursive functions cannot be inferred using rst-order queries in the query language containing extra symbols +; <]. The proof of this theorem involves a new decidability result about Presburger arithmetic which is of independent interest. Using our machinery, we show that the set of all primitive recursive functions cannot be inferred with a bounded number of mind ...

The importance of correct and clear decisions during a complex difficult situation is very easy to understand, but not so achieve. Especially in situations where decision-makers must decide under time pressure uncertainty. For instance, typical crisis have such characteristics. Given the uncertainty, subjectivity ambiguity human knowledge, are also characterized by conflicting interests. In thi...

This paper contributes to the area of inductive logic programming by presenting a new learning framework that allows the learning of weak constraints in Answer Set Programming (ASP). The framework, called Learning from Ordered Answer Sets, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as ordered pairs of partial answer s...

Most of the mathematical models of collective behavior describe uncertainty in individual decision making through additive uniform noise. However, recent data driven studies on animal locomotion indicate that a number of animal species may be better represented by more complex forms of noise. For example, the popular zebrafish model organism has been found to exhibit a burst-and-coast swimming ...

On account of the existence of uncertainty, DEA occasionally faces the situation of imprecise data, especially when a set of DMUs include missing data, ordinal data, interval data, stochastic data, or fuzzy data. Therefore, how to evaluate the efficiency of a set of DMUs in interval environments is a problem worth studying. In this paper, we discussed the new method for evaluation and ranking i...

In the past few years, the statistical relational learning (SRL) community has recognized the importance of combining the strengths of statistical learning and relational learning (also known as inductive logic programming (ILP)), and developed several novel representations, as well as algorithms to learn their parameters and structure. However, the problem of statistical predicate invention (S...

Weaver is a hybrid planning algorithm that can create plans in domains that include uncertainty, modelled either as incomplete knowledge of the initial state of the world, of the effects of plan steps or of the possible external events. The plans are guaranteed to exceed some given threshold probability of success. Weaver creates a Bayesian network representation of a plan to evaluate it, in wh...

This paper reports a psychological study of human categorization that looked at the procedures used by expert scientists when dealing with puzzling items. Five professional botanists were asked to specify a category from a set of positive and negative instances. The target category in the study was defined by a feature that was unusual, hence situations of uncertainty and puzzlement were genera...

Enterprise search technology retrieves digital objects and internally generated content within organizations. Unlike other retrieval environments, enterprise search is a community of practice which responds to expected activity at similar times. Collective mind theory (Weick & Roberts, 2003) is similar to retrieval environments where the unplanned movements of multiple people move towards a sim...