Maximin Safety: When Failing to Lose is Preferable to Trying to Win

We present a new decision rule, \emph{maximin safety}, that seeks to maintain a large margin from the worst outcome, in much the same way minimax regret seeks to minimize distance from the best. We argue that maximin safety is valuable both descriptively and normatively. Descriptively, maximin safety explains the well-known \emph{decoy effect}, in which the introduction of a dominated option changes preferences among the other options. Normatively, we provide an axiomatization that characterizes preferences induced by maximin safety, and show that maximin safety shares much of the same behavioral basis with minimax regret.Comment: 14 page

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Mathematics as the role model for neoclassical economics (Blanqui Lecture)

Born out of the conscious effort to imitate mechanical physics, neoclassical economics ended up in the mid 20th century embracing a purely mathematical notion of rigor as embodied by the axiomatic method. This lecture tries to explain how this could happen, or, why and when the economists’ role model became the mathematician rather than the physicist. According to the standard interpretation, the triumph of axiomatics in modern neoclassical economics can be explained in terms of the discipline’s increasing awareness of its lack of good experimental and observational data, and thus of its intrinsic inability to fully abide by the paradigm of mechanics. Yet this story fails to properly account for the transformation that the word “rigor” itself underwent first and foremost in mathematics as well as for the existence of a specific motivation behind the economists’ decision to pursue the axiomatic route. While the full argument is developed in Giocoli 2003, these pages offer a taste of a (partially) alternative story which begins with the so-called formalist revolution in mathematics, then crosses the economists’ almost innate urge to bring their discipline to the highest possible level of generality and conceptual integrity, and ends with the advent and consolidation of that very core set of methods, tools and ideas that constitute the contemporary image of economics.Axiomatic method, formalism, rationality, neoclassical economics

A novel model to measure supplier performance in the supplier selection process

Supplier evaluation has become a significant topic over the past decades, as companies have started to become more outsourced oriented. However, previous research on this topic has not paid adequate attention to the limitations associated with availability of accurate and reliable data relating to the performance of potential suppliers. In an attempt to address this issue, this paper proposes a novel supplier evaluation model that can handle imprecise quantitative and qualitative data. Additionally, Decision Maker’s opinions regarding both qualitative and quantitative criteria are incorporated into this model so that a more comprehensive and realistic assessment of supplier performance can be achieved. The model combines five separate methods that have specific capabilities to handle multiple limitations in the existing methods: Fuzzy Analytical Hierarchy Process and Fuzzy TOPSIS method are used to analyse qualitative criteria/data; Analytical Hierarchy Process and Axiomatic Design are used to analyse quantitative criteria/data, with a particular focus on handling variability in performance data; and Data Envelopment Analysis is used to integrate the results of the two approaches above so as to comparative assessment of supplier performance. This model is verified using a numerical example

Does Consistency Predict Accuracy of Beliefs?: Economists Surveyed About PSA

Subjective beliefs and behavior regarding the Prostate Specific Antigen (PSA) test for prostate cancer were surveyed among attendees of the 2006 meeting of the American Economic Association. Logical inconsistency was measured in percentage deviations from a restriction imposed by Bayes’ Rule on pairs of conditional beliefs. Economists with inconsistent beliefs tended to be more accurate than average, and consistent Bayesians were substantially less accurate. Within a loss function framework, we look for and cannot find evidence that inconsistent beliefs cause economic losses. Subjective beliefs about cancer risks do not predict PSA testing decisions, but social influences do.logical consistency, predictive accuracy, elicitation, non-Bayesian, ecological rationality

Does consistency predict accuracy of beliefs?: Economists surveyed about PSA

Subjective beliefs and behavior regarding the Prostate Specific Antigen (PSA) test for prostate cancer were surveyed among attendees of the 2006 meeting of the American Economic Association. Logical inconsistency was measured in percentage deviations from a restriction imposed by Bayes’ Rule on pairs of conditional beliefs. Economists with inconsistent beliefs tended to be more accurate than average, and consistent Bayesians were substantially less accurate. Within a loss function framework, we look for and cannot find evidence that inconsistent beliefs cause economic losses. Subjective beliefs about cancer risks do not predict PSA testing decisions, but social influences do.logical consistency, predictive accuracy, elicitation, non-Bayesian, ecological rationality

Design and Evaluation of Ballast Water Management Systems using Modified and Hybridised Axiomatic Design Principles

There are two major motivations to this research. The first is based on the concerns raised at the International Maritime Organisation (IMO) MEPC 67 and 68 meetings regarding the capacity of some type-approved Ballast Water Management (BWM) Systems to meet the performance standard (D-2) of the BWM Convention at-all-times and in all conditions. The second is based on the reluctance expressed by some ship- owners to install the system onboard their ships as a Lloyd\u27s list survey suggested. In this work, an attempt was made to address these issues and concerns using a set of criteria stipulated in Regulation D-5.2 of the BWM Convention which provides the framework for reviewing and evaluating the practical concepts of managing ballast water, developing a conceptual model for managing ballast water and minimizing the contributions of human-error to BWM System performance by analyzing the associated operational human factors. Firstly, the design of a conceptual model of managing ballast water and the evaluation of some established practical concepts of BWM were achieved by using a suitable technique (Axiomatic Design or AD) which was selected via a robust procedure. The two axioms of Axiomatic Design (information and independence) were used to evaluate four different concepts of managing ballast water as well as develop a BWM Convention-compliant conceptual design matrix model respectively. Based on data collected from ballast water management experts, Post-loading Onshore Ballast Water Management System was shown to be the most appropriate ballast water management concept with respect to the Regulation D-5.2 set of criteria. This presents a paradigm shift in expert preference from traditional shipboard systems to onshore systems with respect to the IMO-criteria. The pathway for improved performance of the Convention-compliant design matrix was subsequently determined and prioritised using Sufield model of Altshuler\u27s theory of inventive problem solving (TRIZ). Lastly, a 5-step algorithm was developed to minimise operator errors in the BWM System’s operation. Fatigue and training were found to have the greatest impact on operator performance