Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

Climate change adaptation : a decision support framework to encourage environmentally responsible behaviour

Structured Abstract:
Purpose: Very few studies investigate environmentally responsible behaviour (ERB). This paper presents a new 'Awareness Behaviour Intervention Action' (ABIA) Decision Support Framework to sustain ERB.

Design/methodology/approach: Previous ERB programmes have failed to deliver lasting results; they have not appropriately understood and provided systems to address ERB (Costanzo et al., 1986). These programmes were based on assumptions (Moloney et al., 2010), which this paper addresses. The ABIA Framework has been developed through a case study of social housing tenants waiting for low or zero carbon homes.

Findings: The ABIA Framework enables a better understanding of current attitudes to environmental issues and provides support for ERB alongside technological interventions employed to promote and sustain carbon reduction.

Research limitations/implications: The ABIA Framework should be tested on individuals and communities in a variety of socio-economic, political and cultural contexts. This will help unpack how it can impact on the behaviours of individuals and communities including stakeholders.

Practical implications: This type of research and the ABIA Framework developed from it are crucial if the UK pledge to become the first country in the World where all new homes from 2016 are to be zero carbon.

Social implications: The Framework encourages both individual and community discussion and solving of sustainability issues.

Originality/value: There are few, if any, studies that have developed a framework which can be used to support behavioural change for adaptation to sustainable living in low or zero carbon homes.

“Boundary-setting as a core activity in complex public systems”

Title: Boundary-setting as a core activity in complex public systems
Authors: Joanne Murphy & Mary Lee Rhodes

The definition of the boundary of a system is at the core of any systems approach (Midgley 2000; 2003). By defining boundaries we enable – and delimit – the range of outcomes sought and the actions and resources that can be brought to bear. In complex adaptive systems (CAS) analysis, the conceptualisaion and definition of boundaries is particularly challenging as they are constantly undergoing redefinition through agent action, interaction and entry/exit. (Rhodes et al 2011). The concept of ‘boundaries’ appears regularly in a wide range of literature around public management, administration, geopolitics, regeneration and organisational development. Discussions around boundaries focus on many things from concrete physical manifestations and barriers, to virtual interfaces between one organisational unit and another, or even entirely theoretical demarcations between different schools of thought (Kaboolian, 1998, Levi-Faur, 2004, Agranoff & McGuire, 2004).

However, managing ‘beyond’ such boundaries is a routinely recurring aspiration that transcends sectors and local concerns. Unsurprisingly then, there is an increasing understanding of the need to acknowledge and manage such boundaries (whether they be physical, social or organisational) within public management as a discipline (Currie et al 2007, Fitzsimmons and White, 1997, Murtagh, 2002). This paper explores the impact of boundaries on public management strategic decision-making in the sectors of urban regeneration and healthcare. In particular, it focuses on demarcations to physical space, communal identity and within professional relationships in these sectors.

The first section describes the research that gave rise to the paper and the cases examined. Next we briefly define what we mean by boundaries. We explore issues that have emerged from our analysis of urban regeneration and health care singularly, before looking at how the concept of boundaries is a recurrent concern across the sectors. The main contribution of the paper is an exploration of how a CAS lens can bring a new insight into the concept of boundaries and decision-making in the two sets of case studies. This discussion will concentrate on initial conditions, bifurcation and adaptation as key CAS factors in relation to boundaries. We conclude with a brief discussion on the benefits of a CAS lens to an analysis of boundaries in public management decision-making.
References:

Agranoff, R. and McGuire, M. (2003) Collaborative Public Management: Strategies for Local Government. Washington, DC: Georgetown Univ. Press.

Currie, G., Lockett, A. (2007) “A critique of transformational leadership: moral, professional & contingent dimensions of leadership within public services organizations”. Human Relations 60: 341-370.

Fitzsimmons and White, (1997) "Crossing boundaries: communication between professional groups", Journal of Management in Medicine, Vol. 11 Iss: 2, pp.96 – 101

Kaboolian, L. (1998) “The New Public Management: Challenging the Boundaries of the Management vs. Administration Debate” Public Administration Review Vol. 58, No. 3 pp.189-193

Levi-Faur D. and Vigoda-Gadot Eran (eds) (2004) International Public Policy and Management: Policy Learning Beyond Regional, Cultural and Political Boundaries, Marcel Dekker,
Midgley, G. (ed) (2003) Systems Thinking. London: Sage Publications

Midgley, G. (2000) Systemic Intervention: Philosophy, Methodology and Practice. New York, NY: Kluwer.

Murtagh, B. (2002). The Politics of Territory: Policy and Segregation in Northern Ireland. Basingstoke, Palgrave.

Rhodes, ML, Joanne Murphy, Jenny Muir, John Murray (2011) Public Management & Complexity Theory: Richer Decision Making in Irish Public Services, UK: Routledge

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.

Farmer perception of suitable conditions for slurry application compared with decision support system recommendations

The application of slurry nutrients to land can be associated with unintended losses to the environment depending on soil and weather conditions. Correct timing of slurry application, however, can increase plant nutrient uptake and reduce losses. A decision support system (DSS), which predicts optimum conditions for slurry spreading based on the Hybrid Soil Moisture Deficit (HSMD) model, was investigated for use as a policy tool. The DSS recommendations were compared to farmer perception of suitable conditions for slurry spreading for three soil drainage classes (well, moderate and poorly drained) to better understand on farm slurry management practices and to identify potential conflict with farmer opinion. Six farmers participated in a survey over two and a half years, during which they completed a daily diary, and their responses were compared to Soil Moisture Deficit (SMD) calculations and weather data recorded by on farm meteorological stations. The perception of land drainage quality differed between farmers and was related to their local knowledge and experience. It was found that the allocation of grass fields to HSMD drainage classes using a visual assessment method aligned farmer perception of drainage at the national scale. Farmer opinion corresponded to the theoretical understanding that slurry should not be applied when the soil is wetter than field capacity, i.e. when drainage can occur. While weather and soil conditions (especially trafficability) were the principal reasons given by farmers not to spread slurry, farm management practices (grazing and silage) and current Nitrates Directive policies (closed winter period for spreading) combined with limited storage capacities were obstacles to utilisation of slurry nutrients. Despite the slightly more restrictive advice of the DSS regarding the number of suitable spreading opportunities, the system has potential to address an information deficit that would help farmers to reduce nutrient losses and optimise plant nutrient uptake by improved slurry management. The DSS advice was in general agreement with the farmers and, therefore, they should not be resistant to adopting the tool for day to day management.

Intra-operative decision making by ophthalmic surgeons

Research on surgical decision making and risk management usually focuses on peri-operative care, despite the magnitude and frequency of intra-operative risks. The aim of this study was to examine ophthalmic surgeons' intra-operative decisions and risk management strategies in order to explore differences in cognitive processes.

Bolivian health and social care professionals' experiences of decision-making in oncology and palliative care

In the UK, end-of-life care strategies recommend patients and families are involved in decision making around treatment and care. In Bolivia, such strategies do not exist, and access to oncology services depends on finance, geography, education and culture. Compared to more developed countries, the delivery of oncology services in Latin America may result in a higher percentage of patients presenting with advanced incurable disease. The objective of this study was to explore decision-making experiences of health and social care professionals who cared for oncology and palliative care patients attending the Instituto Oncológico Nacional, Cochabamba (Bolivia). Patients were predominantly from the Quechua tradition, which has its own ethnic diversity, linguistic distinctions and economic systems. Qualitative data were collected during focus groups. Data analysis was conducted using Interpretative Phenomenological Analysis. Three interrelated themes emerged: (i) making sense of structures of experience and relationality; (ii) frustration with the system; and (iii) the challenges of promoting shared decision making. The study uncovered participants' lived experiences, emotions and perceptions of providing care for Quechua patients. There was evidence of structural inequalities, the marginalisation of Quechua patients and areas of concern that social workers might well be equipped to respond to, such as accessing finances for treatment/care, education and alleviating psychological or spiritual suffering.

Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations

This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

Analogies to semantic and syntactic mental labour in the Feist decision

The Supreme Court of the United States in Feist v. Rural (Feist, 1991) specified that compilations or databases, and other works, must have a minimal degree of creativity to be copyrightable. The significance and global diffusion of the decision is only matched by the difficulties it has posed for interpretation. The judgment does not specify what is to be understood by creativity, although it does give a full account of the negative of creativity, as ‘so mechanical or routine as to require no creativity whatsoever’ (Feist, 1991, p.362). The negative of creativity as highly mechanical has particularly diffused globally.

A recent interpretation has correlated ‘so mechanical’ (Feist, 1991) with an automatic mechanical procedure or computational process, using a rigorous exegesis fully to correlate the two uses of mechanical. The negative of creativity is then understood as an automatic computation and as a highly routine process. Creativity is itself is conversely understood as non-computational activity, above a certain level of routinicity (Warner, 2013).

The distinction between the negative of creativity and creativity is strongly analogous to an independently developed distinction between forms of mental labour, between semantic and syntactic labour. Semantic labour is understood as human labour motivated by considerations of meaning and syntactic labour as concerned solely with patterns. Semantic labour is distinctively human while syntactic labour can be directly humanly conducted or delegated to machine, as an automatic computational process (Warner, 2005; 2010, pp.33-41).

The value of the analogy is to greatly increase the intersubjective scope of the distinction between semantic and syntactic mental labour. The global diffusion of the standard for extreme absence of copyrightability embodied in the judgment also indicates the possibility that the distinction fully captures the current transformation in the distribution of mental labour, where syntactic tasks which were previously humanly performed are now increasingly conducted by machine.

The paper has substantive and methodological relevance to the conference themes. Substantively, it is concerned with human creativity, with rationality as not reducible to computation, and has relevance to the language myth, through its indirect endorsement of a non-computable or not mechanical semantics. These themes are supported by the underlying idea of technology as a human construction. Methodologically, it is rooted in the humanities and conducts critical thinking through exegesis and empirically tested theoretical development

References

Feist. (1991). Feist Publications, Inc. v. Rural Tel. Service Co., Inc. 499 U.S. 340.

Warner, J. (2005). Labor in information systems. Annual Review of Information Science and Technology. 39, 2005, pp.551-573.

Warner, J. (2010). Human Information Retrieval (History and Foundations of Information Science Series). Cambridge, MA: MIT Press.

Warner, J. (2013). Creativity for Feist. Journal of the American Society for Information Science and Technology. 64, 6, 2013, pp.1173-1192.

Adaptive uncertain information fusion to enhance plan selection in BDI agent systems

Correctly modelling and reasoning with uncertain information from heterogeneous sources in large-scale systems is critical when the reliability is unknown and we still want to derive adequate conclusions. To this end, context-dependent merging strategies have been proposed in the literature. In this paper we investigate how one such context-dependent merging strategy (originally defined for possibility theory), called largely partially maximal consistent subsets (LPMCS), can be adapted to Dempster-Shafer (DS) theory. We identify those measures for the degree of uncertainty and internal conflict that are available in DS theory and show how they can be used for guiding LPMCS merging. A simplified real-world power distribution scenario illustrates our framework. We also briefly discuss how our approach can be incorporated into a multi-agent programming language, thus leading to better plan selection and decision making.

An Extended Event Reasoning Framework for Decision Support under Uncertainty

To provide in-time reactions to a large volume of surveil- lance data, uncertainty-enabled event reasoning frameworks for CCTV and sensor based intelligent surveillance system have been integrated to model and infer events of interest. However, most of the existing works do not consider decision making under uncertainty which is important for surveillance operators. In this paper, we extend an event reasoning framework for decision support, which enables our framework to predict, rank and alarm threats from multiple heterogeneous sources.

Solving Decision Problems with Limited Information

We present a new algorithm for exactly solving decision-making problems represented as an influence diagram. We do not require the usual assumptions of no forgetting and regularity, which allows us to solve problems with limited information. The algorithm, which implements a sophisticated variable elimination procedure, is empirically shown to outperform a state-of-the-art algorithm in randomly generated problems of up to 150 variables and 10^64 strategies.

Decision Making by Credal Nets

Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets of distributions. This feature makes the model particularly suited for the implementation of classifiers and knowledge-based systems. When working with sets of (instead of single) probability distributions, the identification of the optimal option can be based on different criteria, some of them eventually leading to multiple choices. Yet, most of the inference algorithms for credal nets are designed to compute only the bounds of the posterior probabilities. This prevents some of the existing criteria from being used. To overcome this limitation, we present two simple transformations for credal nets which make it possible to compute decisions based on the maximality and E-admissibility criteria without any modification in the inference algorithms. We also prove that these decision problems have the same complexity of standard inference, being NP^PP-hard for general credal nets and NP-hard for polytrees.