Multi-Party Negotiation When Agents Have Subjective Estimates of Bargaining Powers

This paper presents a method for generating Pareto-optimal solutions in multi-party negotiations. In this iterative method, decision makers (DMs) formulate proposals that yield a minimum payoff to their opponents. Each proposal belongs to the efficient frontier, DMs try to adjust to a common one. In this setting, each DM is supposed to have a given bargaining power. More precisely each DM is supposed to have a subjective estimate of the power of the different parties. We study the convergence of the method, and provide examples where there is no possible agreement resulting from it.

Packet classification by multi-level cutting of the classification space: An algorithmic-architectural solution for IP packet classification in next generation networks

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their non-deterministic performance. Although CAMs are favoured by technology vendors due to their deterministic high lookup rates, they suffer from the problems of high power dissipation and high silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multi-level cutting the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Packet classification by multi-level cutting of the classification space

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs) are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Adaptability in organisms and artifacts: A multi level perspective on adaptive processes

Abstract Adaptability to changing circumstances is a key feature of living creatures. Understanding such adaptive processes is central to developing successful autonomous artifacts. In this paper two perspectives are brought to bear on the issue of adaptability. The first is a short term perspective which looks at adaptability in terms of the interactions between the agent and the environment. The second perspective involves a hierarchical evolutionary model which seeks to identify higher-order forms of adaptability based on the concept of adaptive meta-constructs. Task orientated and agent-centered models of adaptive processes in artifacts are considered from these two perspectives. The former isrepresented by the fitness function approach found in evolutionary learning, and the latter in terms of the concepts of empowerment and homeokinesis found in models derived from the self-organizing systems approach. A meta-construct approach to adaptability based on the identification of higher level meta-metrics is also outlined. 2009 Published by Elsevier B.V.

Adherence to treatment in children and adolescents with cystic fibrosis: a cross-sectional, multi-method study investigating the influence of beliefs about treatment and parental depressive symptoms

BACKGROUND: Adherence to treatment is often reported to be low in children with cystic fibrosis. Adherence in cystic fibrosis is an important research area and more research is needed to better understand family barriers to adherence in order for clinicians to provide appropriate intervention. The aim of this study was to evaluate adherence to enzyme supplements, vitamins and chest physiotherapy in children with cystic fibrosis and to determine if any modifiable risk factors are associated with adherence.

METHODS: A sample of 100 children (≤18 years) with cystic fibrosis (44 male; median [range] 10.1 [0.2-18.6] years) and their parents were recruited to the study from the Northern Ireland Paediatric Cystic Fibrosis Centre. Adherence to enzyme supplements, vitamins and chest physiotherapy was assessed using a multi-method approach including; Medication Adherence Report Scale, pharmacy prescription refill data and general practitioner prescription issue data. Beliefs about treatments were assessed using refined versions of the Beliefs about Medicines Questionnaire-specific. Parental depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale.

RESULTS: Using the multi-method approach 72% of children were classified as low-adherers to enzyme supplements, 59% low-adherers to vitamins and 49% low-adherers to chest physiotherapy. Variations in adherence were observed between measurement methods, treatments and respondents. Parental necessity beliefs and child age were significant independent predictors of child adherence to enzyme supplements and chest physiotherapy, but parental depressive symptoms were not found to be predictive of adherence.

CONCLUSIONS: Child age and parental beliefs about treatments should be taken into account by clinicians when addressing adherence at routine clinic appointments. Low adherence is more likely to occur in older children, whereas, better adherence to cystic fibrosis therapies is more likely in children whose parents strongly believe the treatments are necessary. The necessity of treatments should be reinforced regularly to both parents and children.

Employers, trade unions and concession bargaining in the Irish recession

The issue of concession bargaining between employers and unions during the Great Recession has received little attention in the research literature. This article presents a systematic analysis of the conduct of concession bargaining during the recession in Ireland in the context of three forms of concession bargaining identified in the international literature: integrative concession bargaining, distributive concession bargaining and ultra concession bargaining – each with different but overlapping sets of institutional foundations and implications for employers and trade unions. Drawing on focus groups of managers and union officials and a representative survey of employers, the article shows that distributive concession bargaining has been the predominant form in the Irish recession. This form of concession bargaining is likely to have few lasting direct effects on employer or union roles in collective bargaining but nevertheless appears to have significant indirect implications for the silent marginalization of unions in workplaces.

Recent developments in the Thomson Parabola Spectrometer diagnostic for laser-driven multi-species ion sources

Ongoing developments in laser-driven ion acceleration warrant appropriate modifications to the standard Thomson Parabola Spectrometer (TPS) arrangement in order to match the diagnostic requirements associated to the particular and distinctive properties of laser-accelerated beams. Here we present an overview of recent developments by our group of the TPS diagnostic aimed to enhance the capability of diagnosing multi-species high-energy ion beams. In order to facilitate discrimination between ions with same Z / A , a recursive differential filtering technique was implemented at the TPS detector in order to allow only one of the overlapping ion species to reach the detector, across the entire energy range detectable by the TPS. In order to mitigate the issue of overlapping ion traces towards the higher energy part of the spectrum, an extended, trapezoidal electric plates design was envisaged, followed by its experimental demonstration. The design allows achieving high energy-resolution at high energies without sacrificing the lower energy part of the spectrum. Finally, a novel multi-pinhole TPS design is discussed, that would allow angularly resolved, complete spectral characterization of the high-energy, multi-species ion beams.