Access control : allocating resources to selfish agents

The ultimate goal of an authorisation system is to allocate each user the level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting because on one hand employees need enough access to perform their tasks, while on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally through carelessness, losing the information or being socially engineered to give access to an adversary. With the goal of developing a more dynamic authorisation model, we have adopted a game theoretic framework to reason about the factors that may affect users’ likelihood to misuse a permission at the time of an access decision. Game theory provides a useful but previously ignored perspective in authorisation theory: the notion of the user as a self-interested player who selects among a range of possible actions depending on their pay-offs.

Can compensation be claimed under the standard commercial land and building contract where the property sold has no legally enforceable vehicular access?

This was the question that confronted Wilson J in Jarema Pty Ltd v Michihiko Kato [2004] QSC 451. Facts The plaintiff was the buyer of a commercial property at Bundall. The property comprised a 6 storey office building with a basement car park with 54 car parking spaces. The property was sold for $5 million with the contract being the standard REIQ/QLS form for Commercial Land and Buildings (2nd ed GST reprint). The contract provided for a “due diligence” period. During this period, the buyer’s solicitors discovered that there was no direct access from a public road to the car park entrance. Access to the car park was over a lot of which the Gold Coast City Council was the registered owner under a nomination of trustees, the Council holding the property on trust for car parking and town planning purposes. Due to the absence of a registered easement over the Council’s land, the buyer’s solicitors sought a reduction in the purchase price. The seller would not agree to this. Finally the sale was completed with the buyer reserving its rights to seek compensation.

Access and Quality of Heart Failure Management Programs in Australia

Background/aim In response to the high burden of disease associated with chronic heart failure (CHF), in particular the high rates of hospital admissions, dedicated CHF management programs (CHF-MP) have been developed. Over the past five years there has been a rapid growth of CHF-MPs in Australia. Given the apparent mismatch between the demand for, and availability of CHF-MPs, this paper has been designed to discuss the accessibility to and quality of current CHF-MPs in Australia. Methods The data presented in this report has been combined from the research of the co-authors, in particular a review of the inequities in access to chronic heart failure which utilised geographical information systems (GIS) and the survey of heterogeneity in quality and service provision in Australian. Results Of the 62 CHF-MPs surveyed in this study 93% (58) centres had been located areas that are rated as Highly Accessible. This result indicated that most of the CHF-MPs have been located in capital cities or large regional cities. Six percent (4 CHF-MPs) had been located in Accessible areas which were country towns or cities. No CHF-MPs had been established outside of cities to service the estimated 72,000 individuals with CHF living in rural and remote areas. 16% of programs recruited NYHA Class I patients and of these 20% lacked confirmation (echocardiogram) of their diagnosis. Conclusion Overall, these data highlight the urgent need to provide equitable access to CHF-MP's. When establishing CHF-MPs consideration of current evidence based models to ensure quality in practice.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Exponentiated gradient algorithms for conditional random fields and max-margin Markov Networks

Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore an important problem, and becomes a key factor when learning from very large data sets. This paper describes exponentiated gradient (EG) algorithms for training such models, where EG updates are applied to the convex dual of either the log-linear or max-margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex constraints. We study both batch and online variants of the algorithm, and provide rates of convergence for both cases. In the max-margin case, O(1/ε) EG updates are required to reach a given accuracy ε in the dual; in contrast, for log-linear models only O(log(1/ε)) updates are required. For both the max-margin and log-linear cases, our bounds suggest that the online EG algorithm requires a factor of n less computation to reach a desired accuracy than the batch EG algorithm, where n is the number of training examples. Our experiments confirm that the online algorithms are much faster than the batch algorithms in practice. We describe how the EG updates factor in a convenient way for structured prediction problems, allowing the algorithms to be efficiently applied to problems such as sequence learning or natural language parsing. We perform extensive evaluation of the algorithms, comparing them to L-BFGS and stochastic gradient descent for log-linear models, and to SVM-Struct for max-margin models. The algorithms are applied to a multi-class problem as well as to a more complex large-scale parsing task. In all these settings, the EG algorithms presented here outperform the other methods.

Supportive-expressive group therapy for women with metastatic breast cancer: Improving access for Australian women through use of teleconference

While supportive-expressive group therapy (SEGT) has been found to be effective in significantly reducing distress associated with life-threatening illness, the challenge in Australia is to develop a means of providing supportive interventions to rural women who may be isolated both by the experience of illness and by geographical location. In this study an adaptation of SEGT was provided to women with metastatic breast cancer (n =21), who attended face-to-face or by telephone conference call. Participants showed significant gains on standardised measures of well-being, including a reduction in negative affect and an increase in positive affect, over a 12-month period. A reduction in intrusive and avoidant stress symptoms was also observed over 12 months; however, this difference was not significant. These outcomes suggest that SEGT, delivered in an innovative way within a community setting, may be an effective means of moderating the adverse effects of a diagnosis of metastatic breast cancer while improving access to supportive care for rural women. These results are considered exploratory, as the study did not include a matched control group.

Intermittent access to 20% ethanol induces high ethanol consumption in Long-Evans and Wistar rats

BACKGROUND: There has been some difficulty getting standard laboratory rats to voluntarily consume large amounts of ethanol without the use of initiation procedures. It has previously been shown that standard laboratory rats will voluntarily consume high levels of ethanol if given intermittent-access to 20% ethanol in a 2-bottle-choice setting [Wise, Psychopharmacologia 29 (1973), 203]. In this study, we have further characterized this drinking model. METHODS: Ethanol-naïve Long-Evans rats were given intermittent-access to 20% ethanol (three 24-hour sessions per week). No sucrose fading was needed and water was always available ad libitum. Ethanol consumption, preference, and long-term drinking behaviors were investigated. Furthermore, to pharmacologically validate the intermittent-access 20% ethanol drinking paradigm, the efficacy of acamprosate and naltrexone in decreasing ethanol consumption were compared with those of groups given continuous-access to 10 or 20% ethanol, respectively. Additionally, ethanol consumption was investigated in Wistar and out-bred alcohol preferring (P) rats following intermittent-access to 20% ethanol. RESULTS: The intermittent-access 20% ethanol 2-bottle-choice drinking paradigm led standard laboratory rats to escalate their ethanol intake over the first 5 to 6 drinking sessions, reaching stable baseline consumption of high amounts of ethanol (Long-Evans: 5.1 +/- 0.6; Wistar: 5.8 +/- 0.8 g/kg/24 h, respectively). Furthermore, the cycles of excessive drinking and abstinence led to an increase in ethanol preference and increased efficacy of both acamprosate and naltrexone in Long-Evans rats. P-rats initiate drinking at a higher level than both Long-Evans and Wistar rats using the intermittent-access 20% ethanol paradigm and showed a trend toward a further escalation in ethanol intake over time (mean ethanol intake: 6.3 +/- 0.8 g/kg/24 h). CONCLUSION: Standard laboratory rats will voluntarily consume ethanol using the intermittent-access 20% ethanol drinking paradigm without the use of any initiation procedures. This model promises to be a valuable tool in the alcohol research field.

Mean and variance of estimates of the bispectrum of a harmonic random process-an analysis including leakage effects

Analytical expressions are derived for the mean and variance, of estimates of the bispectrum of a real-time series assuming a cosinusoidal model. The effects of spectral leakage, inherent in discrete Fourier transform operation when the modes present in the signal have a nonintegral number of wavelengths in the record, are included in the analysis. A single phase-coupled triad of modes can cause the bispectrum to have a nonzero mean value over the entire region of computation owing to leakage. The variance of bispectral estimates in the presence of leakage has contributions from individual modes and from triads of phase-coupled modes. Time-domain windowing reduces the leakage. The theoretical expressions for the mean and variance of bispectral estimates are derived in terms of a function dependent on an arbitrary symmetric time-domain window applied to the record. the number of data, and the statistics of the phase coupling among triads of modes. The theoretical results are verified by numerical simulations for simple test cases and applied to laboratory data to examine phase coupling in a hypothesis testing framework