An anytime approximation method for the inverse Shapley value problem

Coalition formation is the process of bringing together two or more agents so as to achieve goals that individuals on their own cannot, or to achieve them more efficiently. Typically, in such situations, the agents have conflicting preferences over the set of possible joint goals. Thus, before the agents realize the benefits of cooperation, they must find a way of resolving these conflicts and reaching a consensus. In this context, cooperative game theory offers the voting game as a mechanism for agents to reach a consensus. It also offers the Shapley value as a way of measuring the influence or power a player has in determining the outcome of a voting game. Given this, the designer of a voting game wants to construct a game such that a players Shapley value is equal to some desired value. This is called the inverse Shapley value problem. Solving this problem is necessary, for instance, to ensure fairness in the players voting powers. However, from a computational perspective, finding a players Shapley value for a given game is #p-complete. Consequently, the problem of verifying that a voting game does indeed yield the required powers to the agents is also #P-complete. Therefore, in order to overcome this problem we present a computationally efficient approximation algorithm for solving the inverse problem. This method is based on the technique of successive approximations; it starts with some initial approximate solution and iteratively updates it such that after each iteration, the approximate gets closer to the required solution. This is an anytime algorithm and has time complexity polynomial in the number of players. We also analyze the performance of this method in terms of its approximation error and the rate of convergence of an initial solution to the required one. Specifically, we show that the former decreases after each iteration, and that the latter increases with the number of players and also with the initial approximation error. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaarnas.org). All rights reserved

Polyhexamethylene Biguanide and Nadifloxacin Self-Assembled Nanoparticles: Antimicrobial Effects against Intracellular Methicillin-Resistant Staphylococcus aureus

The treatment of skin and soft tissue infections caused by methicillin-resistant Staphylococcus aureus (MRSA) remains a challenge, partly due to localization of the bacteria inside the host’s cells, where antimicrobial penetration and efficacy is limited. We formulated the cationic polymer polyhexamethylene biguanide (PHMB) with the topical antibiotic nadifloxacin and tested the activities against intracellular MRSA in infected keratinocytes. The PHMB/nadifloxacin nanoparticles displayed a size of 291.3 ± 89.6 nm, polydispersity index of 0.35 ± 0.04, zeta potential of +20.2 ± 4.8 mV, and drug encapsulation efficiency of 58.25 ± 3.4%. The nanoparticles killed intracellular MRSA, and relative to free polymer or drugs used separately or together, the nanoparticles displayed reduced toxicity and improved host cell recovery. Together, these findings show that PHMB/nadifloxacin nanoparticles are effective against intracellular bacteria and could be further developed for the treatment of skin and soft tissue infections

On efficient procedures for multi-issue negotiation

This paper studies bilateral, multi-issue negotiation between self-interested agents with deadlines. There are a number of procedures for negotiating the issues and each of these gives a different outcome. Thus, a key problem is to decide which one to use. Given this, we study the three main alternatives: the package deal, the simultaneous procedure, and the sequential procedure. First, we determine equilibria for the case where each agent is uncertain about its opponent’s deadline. We then compare the outcomes for these procedures and determine the one that is optimal (in this case, the package deal is optimal for each party). We then compare the procedures in terms of their time complexity, the uniqueness and Pareto optimality of their solutions, and their time of agreement

Evaluation of the resistance of few citrus rootstocks to alkalinity by applying a faste test of secreening

Alkalinity of Moroccan soils is the major abiotic constraint on citrus production area. The best choice of citrus rootstocks adequate and resistant is a better solution to avoid this problem. The aim of this study is to develop a fast test of citrus rootstocks screening towards alkalinity. The alkaline stress was applied on ten citrus rootstocks two month old, using irrigation with a Hoagland and Arnon solution added with 1 g CaCO(3)/L and adjusted at various pH levels 6, 7 and 9. Observations concerned symptoms incidence and severity of iron chlorosis after two months of rearing. Results permitted to classify Poncirus trifoliata and Flying dragon as the most sensitive to alkalinity stresses, whereas, Citrus volkameriana and Citrus macrophylla were resistant. These conclusions are equivalent with those obtained with old citrus rootstocks in field trials

Highlights of the 2nd Bioinformatics Student Symposium by ISCB RSG-UK [version 1]

Following the success of the 1 (st) Student Symposium by ISCB RSG-UK, a 2 (nd) Student Symposium took place on 7 (th) October 2015 at The Genome Analysis Centre, Norwich, UK. This short report summarizes the main highlights from the 2 (nd) Bioinformatics Student Symposium

Kinetically driven helix formation during the homopolymer collapse process

Using Langevin simulations, we find that simple 'generic' bead-and-spring homopolymer chains in a sufficiently bad solvent spontaneously develop helical order during the process of collapsing from an initially stretched conformation. The helix formation is initiated by the unstable modes of the straight chain, which drive the system towards a long-lived metastable transient state. The effect is most pronounced if hydrodynamic interactions are screened.Comment: 4 pages, 4 figure

Acceptance conditions in automated negotiation

In every negotiation with a deadline, one of the negotiating parties has to accept an offer to avoid a break off. A break off is usually an undesirable outcome for both parties, therefore it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When designing such conditions one is faced with the acceptance dilemma: accepting the current offer may be suboptimal, as better offers may still be presented. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. Motivated by the challenges of bilateral negotiations between automated agents and by the results and insights of the automated negotiating agents competition (ANAC), we classify and compare state-of-the-art generic acceptance conditions. We focus on decoupled acceptance conditions, i.e. conditions that do not depend on the bidding strategy that is used. We performed extensive experiments to compare the performance of acceptance conditions in combination with a broad range of bidding strategies and negotiation domains. Furthermore we propose new acceptance conditions and we demonstrate that they outperform the other conditions that we study. In particular, it is shown that they outperform the standard acceptance condition of comparing the current offer with the offer the agent is ready to send out. We also provide insight in to why some conditions work better than others and investigate correlations between the properties of the negotiation environment and the efficacy of acceptance condition

Autonomous UAV for suspicious action detection using pictorial human pose estimation and classification

Visual autonomous systems capable of monitoring crowded areas and alerting the authorities in occurrence of a suspicious action can play a vital role in controlling crime rate. Previous atte mpts have been made to monitor crime using posture recognition but nothing exclusive to investigating actions of people in large populated area has been cited. In order resolve this shortcoming, we propose an autonomous unmanned aerial vehicle (UAV) visual surveillance system that locates humans in image frames followed by pose estimation using weak constraints on position, appearance of body parts and image parsing. The estimated pose, represented as a pictorial structure, is flagged using the proposed Hough Orientation Calculator (HOC) on close resemblance with any pose in the suspicious action dataset. The robustness of the system is demonstrated on videos recorded using a UAV with no prior knowledge of background, lighting or location and scale of the human in the image. The system produces an accuracy of 71% and can also be applied on various other video sources such as CCTV camera