Equational Reasoning as a Tool for Data Analysis

A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.

Reasoning about real-time repetitions: terminating and nonterminating

It is common for a real-time system to contain a nonterminating process monitoring an input and controlling an output. Hence, a real-time program development method needs to support nonterminating repetitions. In this paper we develop a general proof rule for reasoning about possibly nonterminating repetitions. The rule makes use of a Floyd-Hoare-style loop invariant that is maintained by each iteration of the repetition, a Jones-style relation between the pre- and post-states on each iteration, and a deadline specifying an upper bound on the starting time of each iteration. The general rule is proved correct with respect to a predicative semantics. In the case of a terminating repetition the rule reduces to the standard rule extended to handle real time. Other special cases include repetitions whose bodies are guaranteed to terminate, nonterminating repetitions with the constant true as a guard, and repetitions whose termination is guaranteed by the inclusion of a fixed deadline. (C) 2002 Elsevier Science B.V. All rights reserved.

Assessing clinical reasoning: a method to monitor its development in a PBL curriculum

The aim of this study was to develop and trial a method to monitor the evolution of clinical reasoning in a PBL curriculum that is suitable for use in a large medical school. Termed Clinical Reasoning Problems (CRPs), it is based on the notion that clinical reasoning is dependent on the identification and correct interpretation of certain critical clinical features. Each problem consists of a clinical scenario comprising presentation, history and physical examination. Based on this information, subjects are asked to nominate the two most likely diagnoses and to list the clinical features that they considered in formulating their diagnoses, indicating whether these features supported or opposed the nominated diagnoses. Students at different levels of medical training completed a set of 10 CRPs as well as the Diagnostic Thinking Inventory, a self-reporting questionnaire designed to assess reasoning style. Responses were scored against those of a reference group of general practitioners. Results indicate that the CRPs are an easily administered, reliable and valid assessment of clinical reasoning, able to successfully monitor its development throughout medical training. Consequently, they can be employed to assess clinical reasoning skill in individual students and to evaluate the success of undergraduate medical schools in providing effective tuition in clinical reasoning.

Defining civilization utilizing anthropic reasoning

We utilize anthropic reasoning to demonstrate that we are typical observers of our reference class under a self-sampling assumption by investigating the definition of what a civilization is. With reference to the conflict between such reasoning and the observational lack of extra-terrestrial intelligent life, we conclude that a part of our theoretical understanding of the Universe will be at fault.

Logic of Violations: A gentzen systems for reasoning with contrary-to-duty obligations

In this paper we present a Gentzen system for reasoning with contrary-to-duty obligations. The intuition behind the system is that a contrary-to-duty is a special kind of normative exception. The logical machinery to formalise this idea is taken from substructural logics and it is based on the definition of a new non-classical connective capturing the notion of reparational obligation. Then the system is tested against well-known contrary-to-duty paradoxes.

Reasoning algebraically about probabilistic loops

Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calculus. We extend their work to reasoning about probabilistic loops in the probabilistic refinement calculus. We apply our algebraic reasoning to derive transformation rules for probabilistic action systems. In particular we focus on developing data refinement rules for probabilistic action systems. Our extension is interesting since some well known transformation rules that are applicable to standard programs are not applicable to probabilistic ones: we identify some of these important differences and we develop alternative rules where possible. In particular, our probabilistic action system data refinement rules are new.