A More General Theory of Diagnosis from First Principles

Model-based diagnosis has been an active research topic in different communities including artificial intelligence, formal methods, and control. This has led to a set of disparate approaches addressing different classes of systems and seeking different forms of diagnoses. In this paper, we resolve such disparities by generalising Reiter's theory to be agnostic to the types of systems and diagnoses considered. This more general theory of diagnosis from first principles defines the minimal diagnosis as the set of preferred diagnosis candidates in a search space of hypotheses. Computing the minimal diagnosis is achieved by exploring the space of diagnosis hypotheses, testing sets of hypotheses for consistency with the system's model and the observation, and generating conflicts that rule out successors and other portions of the search space. Under relatively mild assumptions, our algorithms correctly compute the set of preferred diagnosis candidates. The main difficulty here is that the search space is no longer a powerset as in Reiter's theory, and that, as consequence, many of the implicit properties (such as finiteness of the search space) no longer hold. The notion of conflict also needs to be generalised and we present such a more general notion. We present two implementations of these algorithms, using test solvers based on satisfiability and heuristic search, respectively, which we evaluate on instances from two real world discrete event problems. Despite the greater generality of our theory, these implementations surpass the special purpose algorithms designed for discrete event systems, and enable solving instances that were out of reach of existing diagnosis approaches

A System for the Diagnosis of Faults using a First Principles Approach

One of the primary areas of application of Artificial Intelligence is diagnosis. Diagnosis from first principles is a diagnostic technique which uses knowledge of the designed structure and function of a device to determine the possible causes of the malfunction. This work builds on the foundation of a theory of diagnosis by implementing and extending the theory. A correction to the algorithm which defines the theory is presented. The theory is extended for multiple sets of observations of the system and measurement data. A fundamental problem in diagnosis is selecting the measurement which will be of the most benefit in reducing the number of competing diagnoses for a system. A heuristic which selects a component whose measurement is likely to be beneficial in isolating the actual diagnosis is also presented

Rules and principles in cognitive diagnoses

Cognitive simulation is concerned with constructing process models of human cognitive behavior. Our work on the ACM system (Automated Cognitive Modeler) is an attempt to automate this process. The basic assumption is that all goal-oriented cognitive behavior involves search through some problem space. Within this framework, the task of cognitive diagnosis is to identify the problem space in which the subject is operating, identify solution paths used by the subject, and find conditions on the operators that explain those solution paths and that predict the subject's behavior on new problems. The work presented in this paper uses techniques from machine learning to automate the tasks of finding solution paths and operator conditions. We apply this method to the domain of multi-column subtraction and present results that demonstrate ACM's ability to model incorrect subtraction strategies. Finally, we discuss the difference between procedural bugs and misconceptions, proposing that errors due to misconceptions can be viewed as violations of principles for the task domain

Fault Localization Models in Debugging

Debugging is considered as a rigorous but important feature of software engineering process. Since more than a decade, the software engineering research community is exploring different techniques for removal of faults from programs but it is quite difficult to overcome all the faults of software programs. Thus, it is still remains as a real challenge for software debugging and maintenance community. In this paper, we briefly introduced software anomalies and faults classification and then explained different fault localization models using theory of diagnosis. Furthermore, we compared and contrasted between value based and dependencies based models in accordance with different real misbehaviours and presented some insight information for the debugging process. Moreover, we discussed the results of both models and manifested the shortcomings as well as advantages of these models in terms of debugging and maintenance.Comment: 58-6

Ebola Scare and Measles Resurgence: Mandatory Isolation/quarantine and Vaccination

Public outcry for radical isolation and quarantine policies followed the first Ebola diagnosis in the United States when Eric Duncan, upon his return home Oct 2014 from West Africa, then in the midst of a catastrophic Ebola epidemic, tested positive for Ebola. Likewise, the Dec 2014 Disneyland measles outbreak unleashed an angry backlash against parents who refused to have their children vaccinated; and there was public momentum to repeal all legal exemptions to mandatory vaccination of school children. This paper presents an ethical and legal analysis to adjudicate the issue which is at stake in both controversies; namely the inherent conflict between individual rights v. public health when the nation is threatened by serious communicable disease. It presents reasoned arguments, weighing duty-based v. consequence-maximizing ethical principles of right action through application of the felicity calculus (net utility). And the paper demonstrates how the metaethical theory of emotivism is operative in formation and expression of public sentiment which fueled the ethical and legal deliberations

Current definitions of “transdiagnostic” in treatment development: A search for consensus

Research in psychopathology has identified psychological processes that are relevant across a range of Diagnostic and Statistical Manual (DSM) mental disorders, and these efforts have begun to produce treatment principles and protocols that can be applied transdiagnostically. However, review of recent work suggests that there has been great variability in conceptions of the term “transdiagnostic” in the treatment development literature. We believe that there is value in arriving at a common understanding of the term “transdiagnostic.” The purpose of the current manuscript is to outline three principal ways in which the term “transdiagnostic” is currently used, to delineate treatment approaches that fall into these three categories, and to consider potential advantages and disadvantages of each approachFirst author draf

The place of expert systems in a typology of information systems

This article considers definitions and claims of Expert Systems ( ES) and analyzes them in view of traditional Information systems (IS). It is argued that the valid specifications for ES do not differ fran those for IS. Consequently the theoretical study and the practical development of ES should not be a monodiscipline. Integration of ES development in classical mathematics and computer science opens the door to existing knowledge and experience. Aspects of existing ES are reviewed from this interdisciplinary point of view

Effective coaching of parents and professionals supporting children who are deaf or hard of hearing

This literature review examines the relationship between collaboration, adult learning and coaching. The most effective adult learning strategies and coaching strategies are discussed to help improve student outcomes for children who are deaf or hard of hearing