Decentralized Computation of Pareto Optimal Pure Nash Equilibria of Boolean Games with Privacy Concerns

In Boolean games, agents try to reach a goal formulated as a Boolean formula. These games are attractive because of their compact representations. However, few methods are available to compute the solutions and they are either limited or do not take privacy or communication concerns into account. In this paper we propose the use of an algorithm related to reinforcement learning to address this problem. Our method is decentralized in the sense that agents try to achieve their goals without knowledge of the other agents’ goals. We prove that this is a sound method to compute a Pareto optimal pure Nash equilibrium for an interesting class of Boolean games. Experimental results are used to investigate the performance of the algorithm.

Achieving optimal dose intensity with adjuvant chemotherapy in elderly breast cancer patients:A 10-year retrospective study in a UK institution

The study was to determine if breast cancer patients aged 65 and above could be given adjuvant chemotherapy safely while achieving an acceptable relative dose intensity of at least 85%. We identified all patients aged 65 and over who received adjuvant chemotherapy over the 10 year period, November 1999 to October 2009, and determined the proportion that achieved a relative dose intensity of at least 85% as well as the tolerability of their treatment. A total of 101 patients were identified, with a median age of 69 years (range 65-78).Of these, 25.7% of patients had at least one major comorbidity, 84.2% had a tumor size of 5 cm or less, 73.3% were node positive and 58.4% were hormone receptor positive. The chemotherapy regimens used were AC (Doxorubicin and Cyclophosphamide), FEC (Fluorouracil, Epirubicin, and Cyclophosphamide), CMF (Cyclophosphamide, Methotrexate, and Fluorouracil) and ECMF (Epirubicin followed by CMF). Seventy-nine patients (78.2%) achieved the relative dose intensity of at least 85%. With respect to toxicity, 11.9% of patients developed febrile neutropenia and 23.8% of patients required hospital admission during the treatment period, but there were no treatment-related deaths in the group. A significant proportion of patients aged 65 and above achieved the intended dose intensity of at least 85% over this 10-year period, with manageable toxicity levels. This supports the use of these regimens as adjuvant chemotherapy for breast cancer in this age group. © 2011 Wiley Periodicals, Inc.

Comparison of optimal designs of steel portal frames including topological asymmetry considering rolled, fabricated and tapered sections

A structural design optimisation has been carried out to allow for asymmetry and fully tapered portal frames. The additional weight of an asymmetric structural shape was found to be on average 5–13% with additional photovoltaic (PV) loading having a negligible effect on the optimum design. It was also shown that fabricated and tapered frames achieved an average percentage weight reduction of 9% and 11%, respectively, as compared to comparable hot-rolled steel frames. When the deflection limits recommended by the Steel Construction Institute were used, frames were shown to be deflection controlled with industrial limits yielding up to 40% saving.

Optimal deployment of geographically distributed workflow engines on the cloud

When orchestrating Web service workflows, the geographical placement of the orchestration engine (s) can greatly affect workflow performance. Data may have to be transferred across long geographical distances, which in turn increases execution time and degrades the overall performance of a workflow. In this paper, we present a framework that, given a DAG-based workflow specification, computes the optimal Amazon EC2 cloud regions to deploy the orchestration engines and execute a workflow. The framework incorporates a constraint model that solves the workflow deployment problem, which is generated using an automated constraint modelling system. The feasibility of the framework is evaluated by executing different sample workflows representative of scientific workloads. The experimental results indicate that the framework reduces the workflow execution time and provides a speed up of 1.3x-2.5x over centralised approaches.