Automating decision making to help establish norm-based regulations

Norms have been extensively proposed as coordination mechanisms for both agent and human societies. Nevertheless, choosing the norms to regulate a society is by no means straightforward. The reasons are twofold. First, the norms to choose from may not be independent (i.e, they can be related to each other). Second, different preference criteria may be applied when choosing the norms to enact. This paper advances the state of the art by modeling a series of decision-making problems that regulation authorities confront when choosing the policies to establish. In order to do so, we first identify three different norm relationships -namely, generalisation, exclusivity, and substitutability- and we then consider norm representation power, cost, and associated moral values as alternative preference criteria. Thereafter, we show that the decision-making problems faced by policy makers can be encoded as linear programs, and hence solved with the aid of state-of-the-art solvers

Online Automated Synthesis of Compact Normative Systems

Peer reviewedPostprin

Full Text and Figure Display Improves Bioscience Literature Search

When reading bioscience journal articles, many researchers focus attention on the figures and their captions. This observation led to the development of the BioText literature search engine [1], a freely available Web-based application that allows biologists to search over the contents of Open Access Journals, and see figures from the articles displayed directly in the search results. This article presents a qualitative assessment of this system in the form of a usability study with 20 biologist participants using and commenting on the system. 19 out of 20 participants expressed a desire to use a bioscience literature search engine that displays articles' figures alongside the full text search results. 15 out of 20 participants said they would use a caption search and figure display interface either frequently or sometimes, while 4 said rarely and 1 said undecided. 10 out of 20 participants said they would use a tool for searching the text of tables and their captions either frequently or sometimes, while 7 said they would use it rarely if at all, 2 said they would never use it, and 1 was undecided. This study found evidence, supporting results of an earlier study, that bioscience literature search systems such as PubMed should show figures from articles alongside search results. It also found evidence that full text and captions should be searched along with the article title, metadata, and abstract. Finally, for a subset of users and information needs, allowing for explicit search within captions for figures and tables is a useful function, but it is not entirely clear how to cleanly integrate this within a more general literature search interface. Such a facility supports Open Access publishing efforts, as it requires access to full text of documents and the lifting of restrictions in order to show figures in the search interface

Automated Synthesis of Compact Normative Systems

Most normative systems make use of explicit representations of norms (namely, obligations, prohibitions, and permissions) and associated mechanisms to support the self-regulation of open societies of self-interested and autonomous agents. A key problem in research on normative systems is that of how to synthesise effective and efficient norms. Manually designing norms is time consuming and error prone. An alternative is to automatically synthesise norms. However, norm synthesis is a computationally complex problem. We present a novel online norm synthesis mechanism, designed to synthesise compact normative systems. It yields normative systems composed of concise (simple) norms that effectively coordinate a multiagent system (MAS) without lapsing into overregulation. Our mechanism is based on a central authority that monitors a MAS, searching for undesired states. After detecting undesirable states, the central authority then synthesises norms aimed to avoid them in the future. We demonstrate the effectiveness of our approach through experimental results

Supply driven mortgage choice

Variable mortgage contracts dominate the UK mortgage market (Miles, 2004). The dominance of the variable rate mortgage contracts has important consequences for the transmission mechanism of monetary policy decisions and systemic risks (Khandani et al., 2012; Fuster and Vickery, 2013). This raises an obvious concern that a mortgage market such as that in the UK, where the major proportion of mortgage debt is either at a variable or fixed for less than two years rate (Badarinza, et al., 2013; CML, 2012), is vulnerable to alterations in the interest rate regime. Theoretically, mortgage choice is determined by demand and supply factors. So far, most of the existing literature has focused on the demand side perspective, and what is limited is consideration of supply side factors in empirical investigation on mortgage choice decisions. This paper uniquely explores whether supply side factors may partially explain observed/ex-post mortgage type decisions. Empirical results detect that lenders’ profit motives and mortgage funding/pricing issues may have assisted in preferences toward variable rate contracts. Securitisation is found to positively impact upon gross mortgage lending volumes while negatively impacting upon the share of variable lending flows. This shows that an increase in securitisation not only improves liquidity in the supply of mortgage funds, but also has the potential to shift mortgage choices toward fixed mortgage debt. The policy implications may involve a number of measures, including reconsideration of the capital requirements for the fixed, as opposed to the variable rate mortgage debt, growing securitisation and optimisation of the mortgage pricing policies

Heterogeneous N2O5 Uptake During Winter: Aircraft Measurements During the 2015 WINTER Campaign and Critical Evaluation of Current Parameterizations

Nocturnal dinitrogen pentoxide (N2O5) heterogeneous chemistry impacts regional air quality and the distribution and lifetime of tropospheric oxidants. Formed from the oxidation of nitrogen oxides, N2O5 is heterogeneously lost to aerosol with a highly variable reaction probability, γ(N2O5), dependent on aerosol composition and ambient conditions. Reaction products include soluble nitrate (HNO3 or NO3−) and nitryl chloride (ClNO2). We report the first‐ever derivations of γ(N2O5) from ambient wintertime aircraft measurements in the critically important nocturnal residual boundary layer. Box modeling of the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the eastern United States derived 2,876 individual γ(N2O5) values with a median value of 0.0143 and range of 2 × 10−5 to 0.1751. WINTER γ(N2O5) values exhibited the strongest correlation with aerosol water content, but weak correlations with other variables, such as aerosol nitrate and organics, suggesting a complex, nonlinear dependence on multiple factors, or an additional dependence on a nonobserved factor. This factor may be related to aerosol phase, morphology (i.e., core shell), or mixing state, none of which are commonly measured during aircraft field studies. Despite general agreement with previous laboratory observations, comparison of WINTER data with 14 literature parameterizations (used to predict γ(N2O5) in chemical transport models) confirms that none of the current methods reproduce the full range of γ(N2O5) values. Nine reproduce the WINTER median within a factor of 2. Presented here is the first field‐based, empirical parameterization of γ(N2O5), fit to WINTER data, based on the functional form of previous parameterizations

Who should be prioritized for renal transplantation?: Analysis of key stakeholder preferences using discrete choice experiments

Background Policies for allocating deceased donor kidneys have recently shifted from allocation based on Human Leucocyte Antigen (HLA) tissue matching in the UK and USA. Newer allocation algorithms incorporate waiting time as a primary factor, and in the UK, young adults are also favoured. However, there is little contemporary UK research on the views of stakeholders in the transplant process to inform future allocation policy. This research project aimed to address this issue. Methods Discrete Choice Experiment (DCE) questionnaires were used to establish priorities for kidney transplantation among different stakeholder groups in the UK. Questionnaires were targeted at patients, carers, donors / relatives of deceased donors, and healthcare professionals. Attributes considered included: waiting time; donor-recipient HLA match; whether a recipient had dependents; diseases affecting life expectancy; and diseases affecting quality of life. Results Responses were obtained from 908 patients (including 98 ethnic minorities); 41 carers; 48 donors / relatives of deceased donors; and 113 healthcare professionals. The patient group demonstrated statistically different preferences for every attribute (i.e. significantly different from zero) so implying that changes in given attributes affected preferences, except when prioritizing those with no rather than moderate diseases affecting quality of life. The attributes valued highly related to waiting time, tissue match, prioritizing those with dependents, and prioritizing those with moderate rather than severe diseases affecting life expectancy. Some preferences differed between healthcare professionals and patients, and ethnic minority and non-ethnic minority patients. Only non-ethnic minority patients and healthcare professionals clearly prioritized those with better tissue matches. Conclusions Our econometric results are broadly supportive of the 2006 shift in UK transplant policy which emphasized prioritizing the young and long waiters. However, our findings suggest the need for a further review in the light of observed differences in preferences amongst ethnic minorities, and also because those with dependents may be a further priority.</p

Surface and Lightning Sources of Nitrogen Oxides over the United States: Magnitudes, Chemical Evolution, and Outflow

We use observations from two aircraft during the ICARTT campaign over the eastern United States and North Atlantic during summer 2004, interpreted with a global 3-D model of tropospheric chemistry (GEOS-Chem) to test current understanding of regional sources, chemical evolution, and export of NOx. The boundary layer NOx data provide top-down verification of a 50% decrease in power plant and industry NOx emissions over the eastern United States between 1999 and 2004. Observed NOx concentrations at 8–12 km altitude were 0.55 ± 0.36 ppbv, much larger than in previous U.S. aircraft campaigns (ELCHEM, SUCCESS, SONEX) though consistent with data from the NOXAR program aboard commercial aircraft. We show that regional lightning is the dominant source of this upper tropospheric NOx and increases upper tropospheric ozone by 10 ppbv. Simulating ICARTT upper tropospheric NOx observations with GEOS-Chem requires a factor of 4 increase in modeled NOx yield per flash (to 500 mol/flash). Observed OH concentrations were a factor of 2 lower than can be explained from current photochemical models, for reasons that are unclear. A NOy-CO correlation analysis of the fraction f of North American NOx emissions vented to the free troposphere as NOy (sum of NOx and its oxidation products) shows observed f = 16 ± 10% and modeled f = 14 ± 9%, consistent with previous studies. Export to the lower free troposphere is mostly HNO3 but at higher altitudes is mostly PAN. The model successfully simulates NOy export efficiency and speciation, supporting previous model estimates of a large U.S. anthropogenic contribution to global tropospheric ozone through PAN export.Earth and Planetary SciencesEngineering and Applied Science

Structural mechanism underpinning cross-reactivity of a CD8(+) T-cell clone that recognizes a peptide derived from human telomerase reverse transcriptase

T-cell cross-reactivity is essential for effective immune surveillance but has also been implicated as a pathway to autoimmunity. Previous studies have demonstrated that T-cell receptors (TCRs) that focus on a minimal motif within the peptide are able to facilitate a high level of T-cell cross-reactivity. However, the structural database shows that most TCRs exhibit less focused antigen binding involving contact with more peptide residues. To further explore the structural features that allow the clonally expressed TCR to functionally engage with multiple peptide-major histocompatibility complexes (pMHCs), we examined the ILA1 CD8(+) T-cell clone that responds to a peptide sequence derived from human telomerase reverse transcriptase. The ILA1 TCR contacted its pMHC with a broad peptide binding footprint encompassing spatially distant peptide residues. Despite the lack of focused TCR-peptide binding, the ILA1 T-cell clone was still cross-reactive. Overall, the TCR-peptide contacts apparent in the structure correlated well with the level of degeneracy at different peptide positions. Thus, the ILA1 TCR was less tolerant of changes at peptide residues that were at, or adjacent to, key contact sites. This study provides new insights into the molecular mechanisms that control T-cell cross-reactivity with important implications for pathogen surveillance, autoimmunity, and transplant rejection

Data mining agent conversations: A qualitative approach to multiagent systems analysis

This paper presents a novel method for analysing the behaviour of multiagent systems on the basis of the semantically rich information provided by agent communication languages and interaction protocols specified at the knowledge level. More low-level communication mechanisms only allow for a quantitative analysis of the occurrence of message types, the frequency of message sequences, and the empirical distributions of parameter values. Quite differently, the semantics of languages and protocols in multiagent systems can help to extract qualitative properties of observed conversations among agents. This can be achieved by interpreting the logical constraints associated with protocol execution paths or individual messages as the context of an observed interaction, and using them as features of learning samples. The contexts “mined ” from such analyses, or context models, can then be used for various tasks, e.g. for predicting others ’ future responses (useful when trying to make strategic communication decisions to achieve a particular outcome), to support ontological alignment (by comparing the properties of logical constraints attached to messages across participating agents), or to assess the trustworthiness of agents (by verifying the logical coherence of their behaviour). This paper details a formal approach that describes our notion of context models in multiagent conversations, an implementation of this approach in a practical tool for mining qualitative context models, and experimental results to illustrate its use and utility. Key words: Agent communication languages, interaction protocols, interaction analysis, dat