Policy Conflict Analysis in Distributed System Management

Accepted versio

Time as a guide to cause

How do people learn causal structure? In two studies we investigated the interplay between temporal order, intervention and covariational cues. In Study 1 temporal order overrode covariation information, leading to spurious causal inferences when the temporal cues were misleading. In Study 2 both temporal order and intervention contributed to accurate causal inference, well beyond that achievable through covariational data alone. Together the studies show that people use both temporal order and interventional cues to infer causal structure, and that these cues dominate the available statistical information. We endorse a hypothesis-driven account of learning, whereby people use cues such as temporal order to generate initial models, and then test these models against the incoming covariational data

The modifier effect and property mutability

The modifier effect is the reduction in perceived likelihood of a generic property sentence, when the head noun is modified. We investigated the prediction that the modifier effect would be stronger for mutable than for central properties, without finding evidence for this predicted interaction over the course of five experiments. However Experiment 6, which provided a brief context for the modified concepts to lend them greater credibility, did reveal the predicted interaction. It is argued that the modifier effect arises primarily from a general lack of confidence in generic statements about the typical properties of unfamiliar concepts. Neither prototype nor classical models of concept combination receive support from the phenomenon

Policy based roles for distributed systems security

Distributed systems are increasingly being used in commercial environments necessitating the development of trustworthy and reliable security mechanisms. There is often no clear informal or formal specification of enterprise authorisation policies and no tools to translate policy specifications to access control implementation mechanisms such as capabilities or Access Control Lists. It is thus difficult to analyse the policy to detect conflicts or flaws and it is difficult to verify that the implementation corresponds to the policy specification. We present in this paper a framework for the specification of management policies. We are concerned with two types of policies: obligations which specify what activities a manager or agent must or must not perform on a set of target objects and authorisations which specify what activities a subject (manager or agent) can or can not perform on the set of target objects. Management policies are then grouped into roles reflecting the organisation..

A facile route to a novel aza-crown ether incorporating three thiophene moieties

The preparation of the first of a novel type of large thiophene-containing aza-crown ether is reported. The macrocycle is synthesised by linking a 3,4-dialkoxythiophene moiety with two 3-hydroxythiophene units and ring closure is effected by reaction with piperazine via the Mannich reaction

Exploring Design Space For An Integrated Intelligent System

Understanding the trade-offs available in the design space of intelligent systems is a major unaddressed element in the study of Artificial Intelligence. In this paper we approach this problem in two ways. First, we discuss the development of our integrated robotic system in terms of its trajectory through design space. Second, we demonstrate the practical implications of architectural design decisions by using this system as an experimental platform for comparing behaviourally similar yet architecturally different systems. The results of this show that our system occupies a "sweet spot" in design space in terms of the cost of moving information between processing components

In situ observations of fish associated with coral reefs off Ireland

The abundance and behaviour of fish on and around coral reefs at Twin Mounds and Giant Mounds, carbonate mounds located on the continental shelf off Ireland (600-1100. m), were studied using two Remotely Operated Vehicle (ROV) dives. We recorded 30 fish taxa on the dives, together with three species of Scleractinia (Lophelia pertusa, Madrepora oculata and Desmophyllum cristagalli) and a diverse range of other corals (Antipatharia, Alcyonacea, and Stylasteridae). Stands of live coral provided the only habitat in which Guttigadus latifrons was observed whereas Neocyttus helgae was found predominantly on structural habitats provided by dead coral. Significantly more fish were found on structurally complex coral rubble habitats than on flatter areas where coral rubble was clogged with sand. The most common species recorded was Lepidion eques (2136 individuals), which always occurred a few cm above bottom and was significantly more active on the reefs than on sedimentary habitats. Synaphobranchus kaupii (1157 indiv.). , N. helgae (198 indiv.) and Micromesistius poutassou (116 indiv.) were also common; S. kaupii did not exhibit habitat-related differences in behaviour, whilst N. helgae was more active over the reefs and other structured habitats whereas M. poutassou was more active with decreasing habitat complexity. Trawl damage and abandoned fishing gear was observed at both sites. We conclude that Irish coral reefs provide complex habitats that are home to a diverse assemblage of fish utilising the range of niches occurring both above and within the reef structure. © 2011 Elsevier Ltd

Beyond Covariation: Cues to Causal Structure

Causal induction has two components: learning about the structure of causal models and learning about causal strength and other quantitative parameters. This chapter argues for several interconnected theses. First, people represent causal knowledge qualitatively, in terms of causal structure; quantitative knowledge is derivative. Second, people use a variety of cues to infer causal structure aside from statistical data (e.g. temporal order, intervention, coherence with prior knowledge). Third, once a structural model is hypothesized, subsequent statistical data are used to confirm, refute, or elaborate the model. Fourth, people are limited in the number and complexity of causal models that they can hold in mind to test, but they can separately learn and then integrate simple models, and revise models by adding and removing single links. Finally, current computational models of learning need further development before they can be applied to human learning